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Paper Citation Record · LEDGER

Semantic Correspondence: Unified Benchmarking and a Strong Baseline

As of 9 August 2026, this Paper Citation Record lists 100 of 138 outbound references and 1 inbound Pith citation observation for arXiv:2505.18060.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.18060 v4

Coverage vector

measured 100 of 138 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:38:28.291480Z

measured 101 of 101 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T02:12:58.506159Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

100 of 138 outbound references displayed

  • verified exact2
  • verified fuzzy29
  • unresolved69
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 37ce696b-feb2-4b48-9d13-d943534d8012 · outbound

This paper cites Sfnet: Learning object-aware semantic correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Sfnet: Learning object-aware semantic correspondence,

Reference 1

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source=pdf_text observed=2026-08-07T14:38:21.307348Z digest=sha256:06cb4cb1cc62cd5bc5a9154b137bb81b8b3c7bdc6ae2cc2af7706b330f82e16d

Observation 5017c1f8-fb9f-4d9b-bf19-320d5401ae2d · outbound

This paper cites Learning semantic correspondence exploiting an object-level prior,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Learning semantic correspondence exploiting an object-level prior,

Reference 2

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Observation 07e6d4a3-e689-4d63-b26b-2f0b8ba799ae · outbound

This paper cites Sift flow: Dense correspondence across scenes and its applications,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Sift flow: Dense correspondence across scenes and its applications,

Reference 3

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Observation ad72cd57-c990-4f95-bd92-e6ba8c78e080 · outbound

This paper cites Reference- based sketch image colorization using augmented-self reference and dense semantic correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Reference- based sketch image colorization using augmented-self reference and dense semantic correspondence,

Reference 4

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Observation f5063aa9-ee70-4d2e-b5de-6aaa1c7959a8 · outbound

This paper cites TokenFlow: Consistent Diffusion Features for Consistent Video Editing.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline TokenFlow: Consistent Diffusion Features for Consistent Video Editing

Reference 5

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source=pdf_text observed=2026-08-07T14:38:21.640366Z digest=sha256:d8e874e1363403587719feb264875689197a5eafa63d0c13af00d3ef85b4493e

Observation 174978af-b7c1-4e64-8a87-fac77170864b · outbound

This paper cites Regiondrag: Fast region-based image editing with diffusion models,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Regiondrag: Fast region-based image editing with diffusion models,

Reference 6

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source=pdf_text observed=2026-08-07T14:38:21.718986Z digest=sha256:b717c46f32f842ff5319e225665fdb3d60ae3694d2391a894968d417bed47bb9

Observation fbc1b5b4-14b1-4006-b6ae-430971a85730 · outbound

This paper cites Neural congealing: Aligning images to a joint semantic atlas,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Neural congealing: Aligning images to a joint semantic atlas,

Reference 7

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Observation d36f69e5-3f05-4754-b58d-84e9976b8e7a · outbound

This paper cites DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Models.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Models

Reference 8

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Observation 85b9c58d-6ddb-4971-8ca7-df5e67a93d19 · outbound

This paper cites Unsupervised object discovery and localization in the wild: Part-based matching with bottom-up region proposals,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Unsupervised object discovery and localization in the wild: Part-based matching with bottom-up region proposals,

Reference 9

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Observation 23ae05df-60ec-4fab-84ea-2e59b335713d · outbound

This paper cites Histograms of oriented gradients for human detection,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Histograms of oriented gradients for human detection,

Reference 10

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Observation b9ac6c49-0e33-4f4c-9399-5c3aa11038a4 · outbound

This paper cites Scnet: Learning semantic correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Scnet: Learning semantic correspondence,

Reference 11

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Observation cfe9d473-11d6-453d-a0c3-f04781f9de70 · outbound

This paper cites Fcss: Fully convolutional self-similarity for dense semantic correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Fcss: Fully convolutional self-similarity for dense semantic correspondence,

Reference 12

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Observation 87545d71-65b2-4f20-90f1-ec2728dd48d5 · outbound

This paper cites Hyperpixel flow: Semantic correspondence with multi-layer neural features,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Hyperpixel flow: Semantic correspondence with multi-layer neural features,

Reference 13

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Observation 37c8f4bd-b737-499d-a61a-e74ed4ca8ae1 · outbound

This paper cites Learning to compose hypercolumns for visual correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Learning to compose hypercolumns for visual correspondence,

Reference 14

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Observation 8cc417d6-b6a5-457c-bebd-84dccffe70d9 · outbound

This paper cites Dynamic context correspondence network for semantic alignment,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Dynamic context correspondence network for semantic alignment,

Reference 15

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source=pdf_text observed=2026-08-07T14:38:22.437973Z digest=sha256:4ae3e63b619339c444ad98659e74aabb5ded6974c9a756093608a3a5ae9ec251

Observation ea775990-c397-4ab1-885e-5213b3501d1d · outbound

This paper cites Efficient semantic matching with hypercolumn correlation,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Efficient semantic matching with hypercolumn correlation,

Reference 16

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source=pdf_text observed=2026-08-07T14:38:22.519116Z digest=sha256:b34c97b7259063808c4e03e923c18dc0619f830887a4f2e8029cf931c78186b9

Observation 08d320ef-960d-4826-be96-3d461a96e432 · outbound

This paper cites Neighbourhood consensus networks,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Neighbourhood consensus networks,

Reference 17

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Observation dd81e4f8-cbbd-448a-89df-c73a19a8fce0 · outbound

This paper cites Correspondence networks with adaptive neighbourhood consensus,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Correspondence networks with adaptive neighbourhood consensus,

Reference 18

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Observation 80941ccf-8dcb-4386-a637-e3cd23977680 · outbound

This paper cites Convolutional hough matching networks,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Convolutional hough matching networks,

Reference 19

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Observation 0c04a5c2-3d4b-43f6-8659-2e3216f5e540 · outbound

This paper cites Patchmatch-based neighborhood consensus for semantic correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Patchmatch-based neighborhood consensus for semantic correspondence,

Reference 20

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Observation c6d5e231-c094-4c25-9e14-22cc6f3d77df · outbound

This paper cites Cats: Cost aggregation transformers for visual correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Cats: Cost aggregation transformers for visual correspondence,

Reference 21

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Observation 53601ace-9e6d-45b0-8d18-0fe60251bb9c · outbound

This paper cites Cats++: Boosting cost aggregation with convolutions and transformers,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Cats++: Boosting cost aggregation with convolutions and transformers,

Reference 22

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Observation a875ab3f-f699-4c6a-8e6b-d38d443d1878 · outbound

This paper cites Transformatcher: Match-to-match attention for semantic correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Transformatcher: Match-to-match attention for semantic correspondence,

Reference 23

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source=pdf_text observed=2026-08-07T14:38:23.155527Z digest=sha256:126f5bf77a69ab4b757d4f57640121fed5ff7375a09eb1913b211e9b3b9786a8

Observation a17e3e0b-6181-43c0-a0f9-5d6c44c26f3c · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline DINOv2: Learning Robust Visual Features without Supervision

Reference 24

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Observation 5c950d78-1e5e-4344-b042-083f490ab3e0 · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline High- resolution image synthesis with latent diffusion models,

Reference 25

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Observation f8207ad1-6953-427e-a9cf-afb241aa78e5 · outbound

This paper cites Emergent correspondence from image diffusion,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Emergent correspondence from image diffusion,

Reference 26

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Observation 00ad5c8f-ff9d-4f5f-b05d-0ce54cba214d · outbound

This paper cites A tale of two features: Stable diffusion complements dino for zero-shot semantic correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline A tale of two features: Stable diffusion complements dino for zero-shot semantic correspondence,

Reference 27

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Observation e93d69af-40e3-41fe-8ad8-bb62092b3234 · outbound

This paper cites Sd4match: Learning to prompt stable diffusion model for semantic matching,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Sd4match: Learning to prompt stable diffusion model for semantic matching,

Reference 28

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source=pdf_text observed=2026-08-07T14:38:23.564772Z digest=sha256:66a495b8d8c4ed7b6ea7494b341a8bb45223ae6028cba869e38d773c37e78eea

Observation 4f552d14-f3bb-4417-9ec3-0019584193b4 · outbound

This paper cites Telling left from right: Identifying geometry-aware semantic correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Telling left from right: Identifying geometry-aware semantic correspondence,

Reference 29

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Observation 4a657f0f-717b-4b22-a1cb-087272e4d3b7 · outbound

This paper cites Distillation of diffusion features for semantic correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Distillation of diffusion features for semantic correspondence,

Reference 30

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Observation 7a8a1af2-ac57-4fd5-b867-b177326351b1 · outbound

This paper cites Hartley and A.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Hartley and A

Reference 31

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Observation 0a89182a-499d-4deb-96ae-05ec8807fb57 · outbound

This paper cites Image matching from handcrafted to deep features: A survey,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Image matching from handcrafted to deep features: A survey,

Reference 32

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Observation 3ba78f83-6d37-4c27-9749-542f4699d698 · outbound

This paper cites A computational theory of human stereo vi- sion,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline A computational theory of human stereo vi- sion,

Reference 33

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Observation e5278ccd-8bd2-4f45-b9c5-b6b4e815d681 · outbound

This paper cites Determining optical flow,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Determining optical flow,

Reference 34

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Observation c5ad0ad6-87c3-4fc8-bbbb-c114969b2229 · outbound

This paper cites Distinctive image features from scale-invariant key- points,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Distinctive image features from scale-invariant key- points,

Reference 35

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Observation 027fb650-1df1-4888-95a1-2618a43f5a44 · outbound

This paper cites A maximum entropy framework for part-based texture and object recognition,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline A maximum entropy framework for part-based texture and object recognition,

Reference 36

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source=pdf_text observed=2026-08-07T14:38:24.123515Z digest=sha256:32f2d41ec4bdab3c0e697e9513647342938bae18dee029587eaaa637b810b82c

Observation f902a284-fe01-4fff-8ee1-87135587361d · outbound

This paper cites Flexible object models for category-level 3d object recognition,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Flexible object models for category-level 3d object recognition,

Reference 37

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source=pdf_text observed=2026-08-07T14:38:24.186538Z digest=sha256:840554f2443d3efedafc05286e52e056bdafa9ffb7df6d79a033fddecf74c6e7

Observation 7bf5a209-d80a-4d94-8068-c8235777c31c · outbound

This paper cites Deformable spatial pyramid matching for fast dense correspondences,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Deformable spatial pyramid matching for fast dense correspondences,

Reference 38

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source=pdf_text observed=2026-08-07T14:38:24.276063Z digest=sha256:c677ee4fbc1a98b188c6bbbcd551eef7deb4dd2794d318d0db4ec121dec63c01

Observation dde6937d-9c4c-4bc8-9b41-0aeba619ce1b · outbound

This paper cites Daisy filter flow: A generalized discrete approach to dense correspondences,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Daisy filter flow: A generalized discrete approach to dense correspondences,

Reference 39

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source=pdf_text observed=2026-08-07T14:38:24.323898Z digest=sha256:a46f2a72da92576d6c3561bb3aec0a9fbee362ac3e1c05795ab4cbf92de5dfac

Observation 94a7bf26-f28a-42f5-9b88-c500b96b5206 · outbound

This paper cites Daisy: An efficient dense descriptor applied to wide-baseline stereo,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Daisy: An efficient dense descriptor applied to wide-baseline stereo,

Reference 40

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:24.427145Z digest=sha256:85d3bbfd551e859e1ce10403faea5ac4016e68e996ba995af0bf7f65859d2c31

Observation 5895b2ff-ae57-4cb0-b143-0208e774dcdf · outbound

This paper cites Dense semantic correspon- dence where every pixel is a classifier,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Dense semantic correspon- dence where every pixel is a classifier,

Reference 43

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:24.621593Z digest=sha256:5d4e5fc37673d04e7c04171806e0b8d32e94e5f71df11ee56f54ead5be3a6dd8

Observation ff04d4f6-4e8e-49b6-b9d5-557432aa2dff · outbound

This paper cites Generalized deformable spatial pyramid: Geometry-preserving dense correspondence estimation,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Generalized deformable spatial pyramid: Geometry-preserving dense correspondence estimation,

Reference 44

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:24.702224Z digest=sha256:50c15b02ae70c65691c02974d9a84cfd6ff39758aa159afa7d2454635efee57e

Observation 92ef763d-40ad-452a-8be7-35f1bfb1bbc4 · outbound

This paper cites Proposal flow,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Proposal flow,

Reference 45

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:24.752318Z digest=sha256:671a9d4e590e485f23dbd1da86356bf6b21695653e307f4849390d93531ca3e6

Observation 4bf3d305-7b09-41b0-bb59-d143ebedc266 · outbound

This paper cites Proposal flow: Semantic correspondences from object propos- als,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Proposal flow: Semantic correspondences from object propos- als,

Reference 46

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no resolver link, observed 2026-08-07T14:38:24.802017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:24.802017Z digest=sha256:d2ce9a6eb5f1fe7ff9c55c0b9b53a5d9c419bc957d61b4e71bb4a29e4830e703

Observation ffcf02a3-d515-46fe-beff-8c00d99060b9 · outbound

This paper cites Object-aware dense semantic correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Object-aware dense semantic correspondence,

Reference 48

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:24.972932Z digest=sha256:923a499720f7f5c352884d94aa15dc12af2b7ce45830c0d645f343c1edb8cadd

Observation c69c1167-7660-4f0a-96e7-0e379bece1aa · outbound

This paper cites A graph-matching kernel for object categorization,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline A graph-matching kernel for object categorization,

Reference 49

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no resolver link, observed 2026-08-07T14:38:25.026061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:25.026061Z digest=sha256:5c66248781cb88a240e176c43a4e12a6e5d226e2ca12a9078c40e8b137193243

Observation d324ee32-d8c0-43f2-b98f-8795ca30e75f · outbound

This paper cites Progressive graph matching: Making a move of graphs via probabilistic voting,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Progressive graph matching: Making a move of graphs via probabilistic voting,

Reference 50

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unresolved
no resolver link, observed 2026-08-07T14:38:25.065330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:25.065330Z digest=sha256:817392847d5ae3f747a540aba6d17aca5333959ae8ce6b0186c134dd1cd73e29

Observation f5e497c6-11b7-48cf-a19d-a2ec800f1d37 · outbound

This paper cites Universal corre- spondence network,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Universal corre- spondence network,

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T14:38:25.146867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:25.146867Z digest=sha256:3b76647f409dfec4495ff920bebc1c2872f4c5a3baee4af1b6b2a4848729e83b

Observation 0e70f114-afe3-4497-8287-5f2fabdc98a1 · outbound

This paper cites Do convnets learn correspon- dence?.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Do convnets learn correspon- dence?

Reference 52

Resolution
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no resolver link, observed 2026-08-07T14:38:25.202934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:25.202934Z digest=sha256:74d12be9e65df5f80545057369562c96885b9cfbad134ce17d00e03d51926d05

Observation 5d05bdbc-6c3d-43f7-a67b-782843f38161 · outbound

This paper cites Hypercolumns for object segmentation and fine-grained localization,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Hypercolumns for object segmentation and fine-grained localization,

Reference 53

Resolution
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no resolver link, observed 2026-08-07T14:38:25.245484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:25.245484Z digest=sha256:078dc911c1135737ceb4934d03a630df301ae02b15151e28a53935b345a8cb51

Observation dcfacf30-6f08-4617-9c96-d8ec1b7e21de · outbound

This paper cites Multi-scale matching networks for semantic correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Multi-scale matching networks for semantic correspondence,

Reference 54

Resolution
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no resolver link, observed 2026-08-07T14:38:25.301739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:25.301739Z digest=sha256:0e12103fcff0bf2b57f1904428595882a2ce5b7c382d0006d96d451819e5f4ff

Observation 8c413614-8be5-4c15-bb5d-747cd2d6ab7e · outbound

This paper cites Independently Keypoint Learning for Small Object Semantic Correspondence.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Independently Keypoint Learning for Small Object Semantic Correspondence

Reference 55

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:38:33.749593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:25.405174Z digest=sha256:ae8973a6d303989e3e1081c234c407efac0029f2f0f0daf737f7c702a293162b

Observation 3543fa47-387a-43dd-b916-714edcb4be34 · outbound

This paper cites Pixel-level semantic correspondence through layout-aware represen- tation learning and multi-scale matching integration,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Pixel-level semantic correspondence through layout-aware represen- tation learning and multi-scale matching integration,

Reference 56

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:25.461189Z digest=sha256:221acfd014398bd6d178e4841c609b0d305ee3c003fc4d010473884cdf7629b8

Observation 3450a0f6-6867-40ab-83f7-c598fabf3a7e · outbound

This paper cites Dif- fusion hyperfeatures: Searching through time and space for semantic correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Dif- fusion hyperfeatures: Searching through time and space for semantic correspondence,

Reference 57

Resolution
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no resolver link, observed 2026-08-07T14:38:25.504486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:25.504486Z digest=sha256:08027ce40cc5408c91b22c2e6dff02dacbe4ffbf8a49704f766b0605ec21c945

Observation de76a8e7-9a6d-4c9e-a2fb-738921efe839 · outbound

This paper cites SimSC: A Simple Framework for Semantic Correspondence with Temperature Learning.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline SimSC: A Simple Framework for Semantic Correspondence with Temperature Learning

Reference 58

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:25.583835Z digest=sha256:6f41928aed1aea52603e953d4d01cf538b2e42894e27926aaeac94e887887c37

Observation 0dad85c0-e649-4ac9-882c-c5615ad378af · outbound

This paper cites Unsupervised semantic correspondence using stable diffusion,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Unsupervised semantic correspondence using stable diffusion,

Reference 59

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no resolver link, observed 2026-08-07T14:38:25.644274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:25.644274Z digest=sha256:51d32519c46e13b94c7c264c482566ad915fd40533fd968b8bfe50e7ab595656

Observation 53a8281a-c411-498a-86b0-09b5ad2b7c7b · outbound

This paper cites Lift: A surprisingly simple lightweight feature transform for dense vit descriptors,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Lift: A surprisingly simple lightweight feature transform for dense vit descriptors,

Reference 60

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:25.695680Z digest=sha256:d8afa404bbae5039e81794c74a16e064a2cbf341d9eae02c27c5e707595cf83a

Observation 79b87236-92b6-4944-98b3-15b275def3f8 · outbound

This paper cites Speech understanding systems: Report of a steering committee,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Speech understanding systems: Report of a steering committee,

Reference 61

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:25.783589Z digest=sha256:cb643d1aa8b9effde91470e3518c22816d4e19300890cdcda8b6c8e6dfeaee9c

Observation 7d8d557d-1c34-4b5d-a5ad-dc3ca68aa3e8 · outbound

This paper cites Feature pyramid networks for object detection,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Feature pyramid networks for object detection,

Reference 62

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:25.845178Z digest=sha256:1799e7ea0124846ba03fc1b310d7a35c0340c4d15abdc282f578de5beb0ae79c

Observation d807aa7f-2ae1-4b55-8545-b76e327e03e5 · outbound

This paper cites An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

Reference 63

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:25.951052Z digest=sha256:b200b85d052639362c6d54d8be57a326729c350ea668840fdbf6de939f61dcec

Observation 1864ca23-1b8b-4ad9-b548-b4b325df5a28 · outbound

This paper cites Zero-shot image feature consensus with deep functional maps,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Zero-shot image feature consensus with deep functional maps,

Reference 64

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:26.009312Z digest=sha256:bac006e6d26bf8d33fd5b6066aad2727a95fa341dac61e87ebfc08e0f1c525cf

Observation 325d0128-ebeb-4cc9-8bd0-38e74b5f2661 · outbound

This paper cites GLU-Net: Global-local universal network for dense flow and correspondences,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline GLU-Net: Global-local universal network for dense flow and correspondences,

Reference 65

Resolution
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no resolver link, observed 2026-08-07T14:38:26.089507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:26.089507Z digest=sha256:a6c2639b4220f96ea41b7f91fe9e98be8b3c1dff2edb273eb066bef610e5d547

Observation db3ef169-06d5-46a1-9b4d-ef6eed109934 · outbound

This paper cites Deep vit features as dense visual descriptors,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Deep vit features as dense visual descriptors,

Reference 66

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:26.157801Z digest=sha256:fc2efb82ee925874798cd66a3a6fe197bce8be443dcac8290fee7b7a4ac28021

Observation aec2bfdb-4311-4121-9446-6fe1414bd67b · outbound

This paper cites Deep semantic feature matching,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Deep semantic feature matching,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:49.661699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:26.270958Z digest=sha256:a7d05482e63a68c6140c824a53dc6b5ce354f4cad350576232a88b8d7b984ea4

Observation 2a4b1a0b-360e-416c-9617-13856c65f950 · outbound

This paper cites Integrative Feature and Cost Aggregation with Transformers for Dense Correspondence.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Integrative Feature and Cost Aggregation with Transformers for Dense Correspondence

Reference 68

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:26.334671Z digest=sha256:30df1a39a02303f509534070e2430188ba615984338f8f4d7826d93567b9d866

Observation 88cf5f4c-f3d6-4840-a6b5-f4dca220dec8 · outbound

This paper cites Warp consistency for unsupervised learning of dense correspondences,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Warp consistency for unsupervised learning of dense correspondences,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:49.453817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:26.433365Z digest=sha256:35b45d888562e1a39632c2daa8f98d3a18711d4bc25f25c36143cf0a4e3d60c2

Observation d3438b22-a3b8-40e3-bc85-81140ba07d90 · outbound

This paper cites Dualrc: A dual-resolution learning framework with neighbourhood consensus for visual corre- spondences,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Dualrc: A dual-resolution learning framework with neighbourhood consensus for visual corre- spondences,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:49.078336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:26.506416Z digest=sha256:6df2197cc259c59596674d5a5d0ab15b06d9c152aa53705ee8a87350f2913764

Observation b37d54c2-6cd7-478b-8f02-04581c558815 · outbound

This paper cites Dual-resolution correspondence networks,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Dual-resolution correspondence networks,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:48.564438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:26.553142Z digest=sha256:4479a4a754f222a38c6331b3b554b860f74355e10ca48dab23ad5a2bdacda949

Observation 8d78f804-071d-4506-acf4-cc457df74b2a · outbound

This paper cites Correspondence transformers with asymmetric feature learning and matching flow super-resolution,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Correspondence transformers with asymmetric feature learning and matching flow super-resolution,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:48.159976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:26.598312Z digest=sha256:e97a3eb8de26169fa4219cbedb0da0cd394f4abe0e614ad7c119fac613e5569f

Observation b602c600-9f44-4469-93c9-91f34dab55b0 · outbound

This paper cites Guided semantic flow,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Guided semantic flow,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:47.739348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:26.639182Z digest=sha256:bd7cfe6bc0062ed32f664c213c75075d7d6978468c54c9c016e4991342564c05

Observation 62318292-2a6e-4ef3-8436-05ed72ad52d7 · outbound

This paper cites Semi- supervised learning of semantic correspondence with pseudo-labels,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Semi- supervised learning of semantic correspondence with pseudo-labels,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:47.505349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:26.689763Z digest=sha256:8c216c25ab63512f52bbf5511fcb5cfef46c63a46bc16eab0d61a49594641b36

Observation 925dd653-dd3e-43f8-b923-1bd8028ee4b1 · outbound

This paper cites Learning semantic correspondence with sparse annotations,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Learning semantic correspondence with sparse annotations,

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:47.197590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:26.741274Z digest=sha256:c3710540cd7f23a2a992beff18fa208573902af7173ed63d8e2be2d89f8d8855

Observation c044d070-68a0-45ae-91e1-856cc7488e4f · outbound

This paper cites Semantic 19 attribute matching networks,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Semantic 19 attribute matching networks,

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:46.917896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:26.798885Z digest=sha256:73713c710bd7db0416f4086af902ea1bf2d1b9bbff9253c001ca7541244e4d79

Observation 8ae14fc8-2fd9-4abf-8cdd-9d70defabf10 · outbound

This paper cites 3×2: 3d object part segmentation by 2d semantic correspondences,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline 3×2: 3d object part segmentation by 2d semantic correspondences,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:46.601482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:26.863184Z digest=sha256:1055343910c2a363e617a42881262e316170d520f4e4db2dc40250b58e44357d

Observation 8c3aa77a-37ba-49c6-bf27-b2289b19d79c · outbound

This paper cites Convolutional hough matching networks for robust and efficient visual correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Convolutional hough matching networks for robust and efficient visual correspondence,

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:46.376421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:26.901936Z digest=sha256:56b403c9c081341eabfef1e39c0531ece4aceb3f80e91723008c38a22fbc9605

Observation 94ed1d8d-256b-476e-abd2-3e0701a3da4b · outbound

This paper cites End-to-end weakly-supervised semantic alignment,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline End-to-end weakly-supervised semantic alignment,

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:46.089021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:26.942508Z digest=sha256:cb3d8b52c70c2f0b3f83c80d5c616205ffb8d95e5b367edbd0f16634c208d138

Observation 61dcfc81-f745-4bff-a0c4-ed995114aba9 · outbound

This paper cites Dctm: Discrete-continuous transformation matching for semantic flow,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Dctm: Discrete-continuous transformation matching for semantic flow,

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:45.800575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:26.981356Z digest=sha256:5237d805aa2c0da01f6efce4b997351c4dc7de6d3e877e6472f6fb52625126dd

Observation 30fa7603-1e0e-4833-8e0f-27e98f2148b1 · outbound

This paper cites Gms: Grid-based motion statistics for fast, ultra-robust feature correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Gms: Grid-based motion statistics for fast, ultra-robust feature correspondence,

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:45.561715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:27.023314Z digest=sha256:5e054d287acdb09b27de2e8b21ecaf61947b1a44d8e895b02e31089fb45c661b

Observation a3b2b5f0-70ab-4fd4-a66b-4a059173afe1 · outbound

This paper cites Improving ransac’s efficiency with a spatial consistency filter [c],.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Improving ransac’s efficiency with a spatial consistency filter [c],

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:45.229806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:27.072641Z digest=sha256:1f20b440e2507a99988c61d7d3f924cd8f845b90a2b36fec5b9488842d4ec39f

Observation c9aeded2-6ff5-4d36-9576-684e88a62a33 · outbound

This paper cites Automated scene matching in movies,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Automated scene matching in movies,

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:44.961236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:27.117945Z digest=sha256:0a9087ca58574c4a9009bbb085eab977d82edf76e74bbf26562c010b2a3657b7

Observation 8eaa1e62-1456-473c-928f-f82646374314 · outbound

This paper cites Video google: A text retrieval approach to object matching in videos,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Video google: A text retrieval approach to object matching in videos,

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:44.698772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:27.173939Z digest=sha256:f774d44baae0c5e75423e15af166bdfa074a44025a2a0ac2bd15569d846443c8

Observation 509003ef-4d82-4046-8b6b-513771ee6e15 · outbound

This paper cites Patchmatch stereo-stereo matching with slanted support windows,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Patchmatch stereo-stereo matching with slanted support windows,

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:44.434149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:27.238097Z digest=sha256:0189150b41287d5050edc07d1c6825217c2b638ac369edd4a05f3271b808c6ea

Observation 9d2907d9-1208-4191-817c-9e79d0cef8c7 · outbound

This paper cites Attention Is All You Need.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Attention Is All You Need

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-07T14:38:27.328379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:27.328379Z digest=sha256:bda95d358b47b4b7c95e864393b8525a8533aa164fc5542180c0d8440573a495

Observation 3e4f8b69-2dff-4b02-990c-870c14f9c476 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-07T14:38:27.391530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:27.391530Z digest=sha256:cc4b6002361d7921c4f9287076ddc5d7a1fdbe0153c47bc174b37c54e6a16d16

Observation 54ebd2ef-55bf-42ab-ae1b-ed60f7a02149 · outbound

This paper cites End-to-end object detection with transformers,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline End-to-end object detection with transformers,

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-07T14:38:27.455144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:27.455144Z digest=sha256:2ecbf9d71b0b739efac4155e13f43033c44c6fce697f82b0f76353c1e0082c78

Observation bfc5b20b-9e42-4999-96c9-8fbb25589d43 · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-07T14:38:27.538654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:27.538654Z digest=sha256:6a9a07f7d62ef265fb78d49e4089cf6f1a1d89fa1793e8bf76e9f61242ea7b8d

Observation f85e8d8a-30ce-431c-8e96-950f4b422168 · outbound

This paper cites Loftr: Detector-free local feature matching with transformers,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Loftr: Detector-free local feature matching with transformers,

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:44.198095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:27.589475Z digest=sha256:02dfd54ebcbb7e5e5c715a03cfef350ab79fc68c6aff540d19aaf91bfa7704c9

Observation 7e24adf3-9872-448e-8502-815363fff1b1 · outbound

This paper cites Cost aggregation with 4D convolutional swin transformer for few-shot segmentation,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Cost aggregation with 4D convolutional swin transformer for few-shot segmentation,

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:43.904591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:27.646975Z digest=sha256:8c1b67f328dbdeff6b30b3433ca1cd161b1250d4287ddb4433478ebb16c7b200

Observation 7fc28435-6497-4aa6-8257-49b80d53f4d4 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-07T14:38:27.706030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:27.706030Z digest=sha256:42824770cd9d859317f1658c3acae475cc2c49a1fec4cd7951c80afa28b92f67

Observation 217dbf63-a26b-4d4c-ae51-dd53fca50828 · outbound

This paper cites Neural matching fields: Implicit representation of matching fields for visual correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Neural matching fields: Implicit representation of matching fields for visual correspondence,

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:43.679425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:27.753141Z digest=sha256:3a532282f26ea37ac839e4df38558420d40533690b06e1b347c91a45f354a97e

Observation df8d1264-ce99-4b4c-ae1e-bea9a6791ef7 · outbound

This paper cites Convolutional neural network architecture for geometric matching,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Convolutional neural network architecture for geometric matching,

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:43.369207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:27.814561Z digest=sha256:d9157497b2d1a2f631c480c1e1f3a5f5d352886221252748b70c26b75b0a7bef

Observation ba7acb1a-646d-4f2c-97f0-5d3089915a9d · outbound

This paper cites Attentive semantic alignment with offset-aware correlation kernels,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Attentive semantic alignment with offset-aware correlation kernels,

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:43.108183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:27.905135Z digest=sha256:45b7e439a05283f9bc280e1fa2df0d3cd38bb458def8819094700f4777a8a573

Observation 87c9e5fc-85c5-4a2c-a719-f7595aae2e52 · outbound

This paper cites Recurrent transformer networks for semantic correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Recurrent transformer networks for semantic correspondence,

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:42.765232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:27.923080Z digest=sha256:51e1c05f418036d1d1b814b5c227d651683b8fc7d493219a5ac5ab7570dc92b1

Observation 69ecf404-775f-412b-932c-2a43c40143b8 · outbound

This paper cites Parn: Pyramidal affine regression networks for dense semantic correspondence,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Parn: Pyramidal affine regression networks for dense semantic correspondence,

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:42.518800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:27.926411Z digest=sha256:5f83b8d6d77677d850a5a572159fc999e0638ce169f80617ce4391f112935aef

Observation 3df23511-ffed-4efe-aada-f634ead4c2ec · outbound

This paper cites Efficient neighbourhood consensus networks via submanifold sparse convolutions,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Efficient neighbourhood consensus networks via submanifold sparse convolutions,

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:42.234244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:27.954842Z digest=sha256:0e78610a1ec9932347ed8af2cf5e71b063c50b0705689ac84d73fe49cb7f699e

Observation d3d0a490-3846-48de-88ee-f5cb47e43b93 · outbound

This paper cites Dkm: Dense kernelized feature matching for geometry estimation,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Dkm: Dense kernelized feature matching for geometry estimation,

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:42.006197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:28.000920Z digest=sha256:a76f55f471b309624c727c3c92d6e4e325527a5139791006bf155f8a3225cb54

Observation eec7a8e9-9f53-4e13-b067-36d4057f3dde · outbound

This paper cites Weakly supervised learning of semantic correspondence through cas- caded online correspondence refinement,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Weakly supervised learning of semantic correspondence through cas- caded online correspondence refinement,

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:41.754879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:28.049667Z digest=sha256:564e0059e96f5b5217fc1ef9edc0754a4946865d7c9f0cbb7e95426fa4730970

Observation 081420eb-0bfb-42df-a2cf-68b86fda0a34 · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Imagenet: A large-scale hierarchical image database,

Reference 101

Resolution
unresolved
no resolver link, observed 2026-08-07T14:38:28.147191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:28.147191Z digest=sha256:4a41719fb680556c7d2287a4378d764f60391c413af147c7b7602b94dbd19c2c

Observation 57bede0f-0ce3-4fad-903a-1dc779d41dbb · outbound

This paper cites FlowWeb: Joint image set alignment by weaving consistent, pixel-wise correspondences,.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline FlowWeb: Joint image set alignment by weaving consistent, pixel-wise correspondences,

Reference 102

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:41.437482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:28.214583Z digest=sha256:d08fc12607c4176881c5bd6e4ce18080d9e70ef43a7b00260bbc9d1ed72e9e8b

Observation 90c6c652-9245-4d8e-9014-0d93f91cc145 · outbound

This paper cites Semantic Matching by Weakly Supervised 2D Point Set Registration.

Semantic Correspondence: Unified Benchmarking and a Strong Baseline Semantic Matching by Weakly Supervised 2D Point Set Registration

Reference 103

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:38:33.431925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:38:28.291480Z digest=sha256:cec2557ba1fc8d55965785243f4703bebdba05bfc515b8805a7e395caf9eeaea

Pith citing papers

Observation 3f45333d-ba22-48a8-abd7-24c2913faaa5 · inbound

Emergent Region-Level Facial Correspondence in Frozen Vision Foundation Models cites this paper.

Emergent Region-Level Facial Correspondence in Frozen Vision Foundation Models Semantic Correspondence: Unified Benchmarking and a Strong Baseline

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-02T02:12:58.506159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T02:12:58.506159Z digest=sha256:4edf64fab9f624597d7a9e35e9b76cccaeb81160ed1e8f5a1badfc880807ee5c