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Paper Citation Record · LEDGER

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting

As of 10 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2607.02139.

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

pith.paper-citation-record.v1
2607.02139 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-03T15:29:40.807911Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

57 of 57 outbound references displayed

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External citation measurements

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Outbound references

Observation 71a2090d-0397-4111-90b4-ed2f1c84d716 · outbound

This paper cites Open-world text-specifed object counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Open-world text-specifed object counting

Reference 1

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Observation b581eeab-403c-4839-8ced-23e316c7fd45 · outbound

This paper cites Countgd: Multi-modal open-world counting.Advances in Neural In- formation Processing Systems, 37:48810–48837, 2024.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Countgd: Multi-modal open-world counting.Advances in Neural In- formation Processing Systems, 37:48810–48837, 2024

Reference 2

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Observation d3d9702f-af47-4316-93c1-005b2934d8cd · outbound

This paper cites Countgd++: Gen- eralized prompting for open-world counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Countgd++: Gen- eralized prompting for open-world counting

Reference 3

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Observation 33a08891-32f8-4081-ae13-edee06388e91 · outbound

This paper cites Open-world ob- ject counting in videos.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Open-world ob- ject counting in videos

Reference 4

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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.

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Observation 401831d9-acb6-4aa6-a6b1-7a0380a6a830 · outbound

This paper cites Completely self-supervised crowd counting via distribution matching.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Completely self-supervised crowd counting via distribution matching

Reference 5

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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.

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Observation af9cfde5-9fdb-4c48-9dee-a6c7b2760692 · outbound

This paper cites Unveiling visual perception in language models: An attention head analysis approach.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Unveiling visual perception in language models: An attention head analysis approach

Reference 6

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Observation ff2411b4-f314-4f40-a638-892ea4cceb62 · outbound

This paper cites Perception encoder: The best visual embeddings are not at the output of the net- work.Advances in Neural Information Processing Systems, 38:60884–60937, 2026.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Perception encoder: The best visual embeddings are not at the output of the net- work.Advances in Neural Information Processing Systems, 38:60884–60937, 2026

Reference 7

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Source-reported events for the cited work

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Observation ef57db69-772f-41e6-a4f5-afa25d750442 · outbound

This paper cites A vehicle counts by class framework using distinguished regions tracking at mul- tiple intersections.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting A vehicle counts by class framework using distinguished regions tracking at mul- tiple intersections

Reference 8

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Observation 20342661-5c84-4c7e-bc1d-5660cd219f12 · outbound

This paper cites Sam 3: Segment anything with concepts.The Fourteenth International Conference on Learning Representations., 2026.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Sam 3: Segment anything with concepts.The Fourteenth International Conference on Learning Representations., 2026

Reference 9

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Observation e17237e3-3176-4c64-8bc2-103c07515737 · outbound

This paper cites Mind the prompt: A novel benchmark for prompt-based class-agnostic counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Mind the prompt: A novel benchmark for prompt-based class-agnostic counting

Reference 10

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Observation ee496ce2-ac0c-45c1-92d6-d0ae8a239534 · outbound

This paper cites Constructive distortion: Improving MLLMs with attention-guided image warping.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Constructive distortion: Improving MLLMs with attention-guided image warping

Reference 11

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Observation 121d8bfc-faa1-4fbe-abab-928923f2002c · outbound

This paper cites Afreeca: Annotation-free counting for all.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Afreeca: Annotation-free counting for all

Reference 12

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Source-reported events for the cited work

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Observation dd740d65-9fb0-4b1c-9887-f764586245b2 · outbound

This paper cites Image retargeting using mesh parametrization.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Image retargeting using mesh parametrization

Reference 13

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Source-reported events for the cited work

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Observation 48e43d99-0f2d-479e-aab0-4a9669fbe707 · outbound

This paper cites Few-shot object counting with dynamic similarity-aware in latent space.IEEE Transactions on Geoscience and Remote Sensing, 62:1–14, 2024.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Few-shot object counting with dynamic similarity-aware in latent space.IEEE Transactions on Geoscience and Remote Sensing, 62:1–14, 2024

Reference 14

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Observation 43819a5f-79e3-429f-bf23-4402189983b6 · outbound

This paper cites Learning to count anything: Reference-less class-agnostic counting with weak supervision.Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Learning to count anything: Reference-less class-agnostic counting with weak supervision.Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Reference 15

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Observation 78c5153d-5bc4-48ed-8ed8-ba73f10c9fde · outbound

This paper cites Drone- based object counting by spatially regularized regional pro- posal network.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Drone- based object counting by spatially regularized regional pro- posal network

Reference 16

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Source-reported events for the cited work

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Observation 64a946c6-4030-47a8-b3fd-09257dbeed01 · outbound

This paper cites Interac- tive class-agnostic object counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Interac- tive class-agnostic object counting

Reference 17

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Observation 289da7dd-a355-4550-a4ae-5435fbb28b86 · outbound

This paper cites Point segment and count: A gener- alized framework for object counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Point segment and count: A gener- alized framework for object counting

Reference 18

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Observation 237733e1-f3f9-4482-99bb-74266e887bf8 · outbound

This paper cites Class- agnostic object counting with text-to-image diffusion model.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Class- agnostic object counting with text-to-image diffusion model

Reference 19

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Observation 1fc9836c-ce59-45b8-9546-57f4319920e2 · outbound

This paper cites Clip- count: Towards text-guided zero-shot object counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Clip- count: Towards text-guided zero-shot object counting

Reference 20

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Source-reported events for the cited work

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Observation edc5bfa0-2378-4c11-98e5-7544e2e87676 · outbound

This paper cites Vlcounter: Text-aware visual representation for zero- shot object counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Vlcounter: Text-aware visual representation for zero- shot object counting

Reference 21

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Observation e8750745-2477-4115-8903-8210d8a21ae5 · outbound

This paper cites Energy- based image deformation.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Energy- based image deformation

Reference 22

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Observation 69a52b9b-73aa-4b15-a333-fe61586b88cf · outbound

This paper cites Segment any- thing.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Segment any- thing

Reference 23

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Observation b8fac23d-e4b9-4532-bf93-4028b4d2b4e2 · outbound

This paper cites Calibrating uncertainty for semi-supervised crowd counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Calibrating uncertainty for semi-supervised crowd counting

Reference 24

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Source-reported events for the cited work

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Observation 35753df3-1a94-4879-b094-d2384e7ccaa4 · outbound

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AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Unresolved cited work

Reference 25

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Observation a76ca56b-956d-415f-a142-ef9afd668acf · outbound

This paper cites A simple-but-effective baseline for training-free class- agnostic counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting A simple-but-effective baseline for training-free class- agnostic counting

Reference 26

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Observation 881f2388-c8a4-4667-b041-65e87e25248b · outbound

This paper cites Improved baselines with visual instruction tuning.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Improved baselines with visual instruction tuning

Reference 27

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Source-reported events for the cited work

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Observation 836ede25-8154-430e-90f3-2b01005c22c4 · outbound

This paper cites Grounding dino: Marrying dino with grounded pre-training for open-set object detection.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Grounding dino: Marrying dino with grounded pre-training for open-set object detection

Reference 28

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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.

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Observation de955be7-19c9-49f7-a400-b6572891d31d · outbound

This paper cites Countse: Soft exemplar open-set object counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Countse: Soft exemplar open-set object counting

Reference 29

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Source-reported events for the cited work

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Observation dcd3e726-532d-4c86-acd9-208d32cbcc49 · outbound

This paper cites Can SAM Count Anything? An Empirical Study on SAM Counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Can SAM Count Anything? An Empirical Study on SAM Counting

Reference 30

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Source-reported events for the cited work

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Observation 85b54735-fbec-4666-a248-8e5eccd56c07 · outbound

This paper cites Through the magnifying glass: Adaptive perception magnification for hallucination-free vlm decoding.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Through the magnifying glass: Adaptive perception magnification for hallucination-free vlm decoding

Reference 31

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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.

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Observation 66f8134f-2ba2-47c0-b41b-c1d7dd18c8ef · outbound

This paper cites Omnicount: Multi-label object counting with semantic- geometric priors.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Omnicount: Multi-label object counting with semantic- geometric priors

Reference 32

Resolution
verified fuzzy
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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=2026-07-03T15:29:40.807911Z digest=sha256:f28f1450e9511009273ef2a8ba8c92af49ebe61d763ff19a2d8f03e7180665f7

Observation 3042ea3c-c5af-415e-99ca-d8ed8841a6d2 · outbound

This paper cites Few-shot object counting and detection.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Few-shot object counting and detection

Reference 33

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verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.038260Z

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=2026-07-03T15:29:40.807911Z digest=sha256:8f31277aabd882deb02bdb47bb063faaa1591d2a2223d46c21c5d91be0015869

Observation 29a537a9-118e-4fe9-b8fe-2295c38a2d74 · outbound

This paper cites Sam3count for zero-shot open vocabulary counting in images and videos.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Sam3count for zero-shot open vocabulary counting in images and videos

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.091549Z

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=2026-07-03T15:29:40.807911Z digest=sha256:cffbaddc1d557f1830e1a6798acc8d2e9029a8adf069fb8ca5dc5bd4d220bbb4

Observation a9769e15-c59c-4cf7-ac5e-fb4979b3be6a · outbound

This paper cites Count- ingdino: A training-free pipeline for class-agnostic count- ing using unsupervised backbones.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Count- ingdino: A training-free pipeline for class-agnostic count- ing using unsupervised backbones

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.089200Z

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=2026-07-03T15:29:40.807911Z digest=sha256:e17de942693de3a9be774cae3d375cff53293b0b36a27488be775c0c0d96a9ea

Observation 27c3d686-7e3c-4753-8013-ff6950ea9c27 · outbound

This paper cites Count-ception: Counting by fully convolutional redundant counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Count-ception: Counting by fully convolutional redundant counting

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.097485Z

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=2026-07-03T15:29:40.807911Z digest=sha256:98ec1debe8a4d1c5fc6e58b55f673084bba474c21c75b790930c27b9ecc9633d

Observation dc89f42b-39d0-4134-beff-14897faaecb5 · outbound

This paper cites A novel unified architecture for low-shot counting by detection and segmentation.Advances in Neural Information Processing Systems, 37:66260–66282, 2024.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting A novel unified architecture for low-shot counting by detection and segmentation.Advances in Neural Information Processing Systems, 37:66260–66282, 2024

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.096680Z

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=2026-07-03T15:29:40.807911Z digest=sha256:9d692bf4740d88120527a9ffd935d4b14f350b2348743186f3c2b97ae389ad9f

Observation 984593da-9093-45da-a36a-f6c9c0cb5657 · outbound

This paper cites Dave-a detect-and-verify paradigm for low-shot counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Dave-a detect-and-verify paradigm for low-shot counting

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.078137Z

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=2026-07-03T15:29:40.807911Z digest=sha256:eb8a16127bf0ba537b53a42f76bfd39ebadf4d06cd75a6d10ea9559e99a40e89

Observation e11e9c31-486c-4759-8cd9-2b59c35f9b5a · outbound

This paper cites T2icount: Enhancing cross-modal understanding for zero-shot counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting T2icount: Enhancing cross-modal understanding for zero-shot counting

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.082067Z

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=2026-07-03T15:29:40.807911Z digest=sha256:dc0ac53b3996e8316629b7012df2a806f4c295f3f1fffeb60928c7c31e766b45

Observation 0fcba8f3-f2fb-4bb9-a590-cfe35ecbe5b5 · outbound

This paper cites Deep count: fruit counting based on deep simulated learning.Sensors, 17(4): 905, 2017.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Deep count: fruit counting based on deep simulated learning.Sensors, 17(4): 905, 2017

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.099015Z

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=2026-07-03T15:29:40.807911Z digest=sha256:9336361285d7ac947e32d3a365be84b7f231762f69e69bb4cb8e1056fa1d622c

Observation c5ce4282-60fd-4d94-8353-edabadcf387e · outbound

This paper cites Learning to count everything.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Learning to count everything

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.076958Z

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=2026-07-03T15:29:40.807911Z digest=sha256:2630b20469b5431debff573c3f84e4a753016eee06afbd9b507c5241d5ff54ce

Observation 2bb26f41-074b-4f5c-a6a6-3e65cc27c2a4 · outbound

This paper cites A comparative study of image retargeting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting A comparative study of image retargeting

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.110882Z

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=2026-07-03T15:29:40.807911Z digest=sha256:53b126eb978235fa14ff513b74f797b0faa14b7b1e5b9a093fdf3a667d70176d

Observation df73f4f4-1a64-4ebb-a007-9d0a6b883d6f · outbound

This paper cites Training-free ob- ject counting with prompts.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Training-free ob- ject counting with prompts

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.069259Z

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=2026-07-03T15:29:40.807911Z digest=sha256:4d687c66881cfa25677fad4d47e1c316fe73f487f3d323008f0750d9cbf800fe

Observation c9c083a9-4283-4696-b5a3-17cc6213ed4a · outbound

This paper cites Persense: Training-free personalized instance segmentation in dense images.BMVC, 2025.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Persense: Training-free personalized instance segmentation in dense images.BMVC, 2025

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.105235Z

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=2026-07-03T15:29:40.807911Z digest=sha256:18870ef76ca772ff3f4dd49a88e34374870fbf15b746f25b3206e24cefd69596

Observation 3b46efa2-df28-4850-82aa-d1f0c10028b7 · outbound

This paper cites Learning to resize images for computer vision tasks.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Learning to resize images for computer vision tasks

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.076026Z

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=2026-07-03T15:29:40.807911Z digest=sha256:8911a67726a5b375e9274e2bad529cae358b17b0cdc6f9f4c285969569f28bb9

Observation d924b1a4-063b-4b8d-b3e7-5b620fdb0050 · outbound

This paper cites Degpr: Deep guided posterior regularization for multi-class cell de- tection and counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Degpr: Deep guided posterior regularization for multi-class cell de- tection and counting

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.109057Z

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=2026-07-03T15:29:40.807911Z digest=sha256:ac9ab5c8f751767a3f7cbb7ab587f8190dcf921afa909883c85b1819e8bb65e1

Observation 028bf547-5c90-4426-a0b8-97968c230a30 · outbound

This paper cites Zero-shot object counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Zero-shot object counting

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.103067Z

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=2026-07-03T15:29:40.807911Z digest=sha256:35c1e86c048756d0c8a35f4415272894b41f31ae3ec2c39d8e3c5faa78e65ec2

Observation b27b18f9-ff21-49dc-b91c-f2ce4d2dee4c · outbound

This paper cites Class-agnostic few-shot object counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Class-agnostic few-shot object counting

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.139436Z

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=2026-07-03T15:29:40.807911Z digest=sha256:c7414dbff811d4fa3405d634fd229c97c568b60dcb7616714702cb4107ba3fc9

Observation 688b2573-f074-448f-806c-4c8b866bbe5c · outbound

This paper cites Content-driven retargeting of stereoscopic images.IEEE Signal Processing Letters, 20(5):519–522, 2013.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Content-driven retargeting of stereoscopic images.IEEE Signal Processing Letters, 20(5):519–522, 2013

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.047625Z

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=2026-07-03T15:29:40.807911Z digest=sha256:b7857e7bd4b9aa42a5f00d716e3a93689f36f797fd6186345a218a1677d6ac0a

Observation b18ed4a6-b762-4895-a185-eb0fe9e48002 · outbound

This paper cites Few-shot object counting with similarity-aware feature enhancement.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Few-shot object counting with similarity-aware feature enhancement

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.061599Z

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=2026-07-03T15:29:40.807911Z digest=sha256:a11eea99f9ac80b4168d865b24f1fba9da8cbf57e9460c714de9216a92608741

Observation 346a6398-5c44-49d0-8e02-2d436ec09294 · outbound

This paper cites Yolo-count: Differentiable object counting for text-to-image generation.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Yolo-count: Differentiable object counting for text-to-image generation

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.063359Z

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=2026-07-03T15:29:40.807911Z digest=sha256:942f80a7dfad5635b7538b9afa6fd876ffba3d6d3cec62115847b0c421a5e006

Observation 7ccd8ff5-9350-4ed6-b628-89a5f79d8970 · outbound

This paper cites Zero-shot object counting with vision-language prior guid- ance network.IEEE Transactions on Circuits and Systems for Video Technology, 2024.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Zero-shot object counting with vision-language prior guid- ance network.IEEE Transactions on Circuits and Systems for Video Technology, 2024

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.062623Z

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=2026-07-03T15:29:40.807911Z digest=sha256:4d569f139d409c578fd748aa318c2bc87d3561bb68ab61f88800c3688369c1b3

Observation f30b24cf-f2b8-4221-ac29-b5021892d32b · outbound

This paper cites Boosting quantitive and spatial awareness for zero-shot object counting.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Boosting quantitive and spatial awareness for zero-shot object counting

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.055705Z

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=2026-07-03T15:29:40.807911Z digest=sha256:f9f80c384776c7abaf4ea92d9508c493e583639a5d56494b159ab2d5117c3166

Observation 21314167-eb40-43fd-8168-56fa9a723471 · outbound

This paper cites Personalize segment anything model with one shot.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Personalize segment anything model with one shot

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.045529Z

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=2026-07-03T15:29:40.807911Z digest=sha256:38f96127a1a0c42ca0ece26252650e993993430f5ebdaaa8dd4b8812028a627a

Observation 3981cc35-d880-4cee-8c3d-9f5d4ab9d81c · outbound

This paper cites Enhancing zero-shot object counting via text-guided local ranking and number- evoked global attention.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Enhancing zero-shot object counting via text-guided local ranking and number- evoked global attention

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.041586Z

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=2026-07-03T15:29:40.807911Z digest=sha256:46aef849db85783b29cdab47552e586c14b89c06c74de22e55ed40e84027f0e1

Observation 73fa001c-d8cb-44a5-99d8-c274029dc62f · outbound

This paper cites Instance-warp: Saliency guided image warping for unsuper- vised domain adaptation.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting Instance-warp: Saliency guided image warping for unsuper- vised domain adaptation

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.053596Z

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=2026-07-03T15:29:40.807911Z digest=sha256:f27bda3cf0a4d9222aad7b5c60ffd26c2906c272f2a8be9f9711aa87b81c4b90

Observation 432aa6b1-e4c3-47be-9208-b21f82ddacbe · outbound

This paper cites apple” , GT:157 Count: 141 Spatial WarpingSimilarity Map Count: 159“stamp.

AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting apple” , GT:157 Count: 141 Spatial WarpingSimilarity Map Count: 159“stamp

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T06:20:45.057789Z

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=2026-07-03T15:29:40.807911Z digest=sha256:8b81102a6b5e932d60b60834515a6e6a7cd2e6c2e86a5248d381ef58df0fa90c

Pith citing papers

No inbound Pith citation observations are available.