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Paper Citation Record · LEDGER

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes

As of 8 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 0 inbound Pith citation observations for arXiv:2508.02157.

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

pith.paper-citation-record.v1
2508.02157 v1

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:14:36.973376Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

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

63 of 63 outbound references displayed

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  • verified fuzzy49
  • unresolved14
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c75eca5b-3add-4908-a582-fc3522310408 · outbound

This paper cites Deep ViT Features as Dense Visual Descriptors.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Deep ViT Features as Dense Visual Descriptors

Reference 1

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Unavailable: canonical work link unavailable.

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Observation 7b8975e8-e3e6-42b4-9971-7613bd7573f1 · outbound

This paper cites Nemo: Neural mesh models of contrastive features for robust 3d pose estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Nemo: Neural mesh models of contrastive features for robust 3d pose estimation

Reference 2

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Observation 7652c038-ab59-46f4-b67d-545c6cc0a7e4 · outbound

This paper cites Coke: Contrastive learning for robust keypoint detec- tion.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Coke: Contrastive learning for robust keypoint detec- tion

Reference 3

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Observation 936d7142-21ea-4f52-98e3-76ce57ccbdd8 · outbound

This paper cites Graph-cut RANSAC.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Graph-cut RANSAC

Reference 4

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Observation ea78549b-693c-4268-86f9-4fb8a974907f · outbound

This paper cites Progressive-x: Efficient, anytime, multi-model fitting algorithm.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Progressive-x: Efficient, anytime, multi-model fitting algorithm

Reference 5

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Observation 0b9886e6-532e-4ef6-972b-ab172c213e7c · outbound

This paper cites Point pair features based object detection and pose estimation revisited.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Point pair features based object detection and pose estimation revisited

Reference 6

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4ed2ad6a-f466-437e-a29c-032f52d93f5a · outbound

This paper cites EfficientPose: An efficient, accurate and scalable end-to-end 6D multi object pose estimation approach.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes EfficientPose: An efficient, accurate and scalable end-to-end 6D multi object pose estimation approach

Reference 7

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Unavailable: canonical work link unavailable.

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Observation ac5cc8c3-c8c4-482f-938a-663aa1da206a · outbound

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

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes End-to- end object detection with transformers

Reference 8

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Observation 9f13cff1-6c51-4e4d-bc44-71885969606f · outbound

This paper cites Sgpa: Structure-guided prior adapta- tion for category-level 6d object pose estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Sgpa: Structure-guided prior adapta- tion for category-level 6d object pose estimation

Reference 9

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 672b35b9-edd1-49d7-bec8-0b577582ec03 · outbound

This paper cites Adaptformer: Adapting vision transformers for scalable visual recognition.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Adaptformer: Adapting vision transformers for scalable visual recognition

Reference 10

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 314889e8-3c87-434b-96c0-26b61061821f · outbound

This paper cites Pointposenet: Point pose network for robust 6d object pose estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Pointposenet: Point pose network for robust 6d object pose estimation

Reference 11

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b0e55f2a-629c-46e7-806b-09714022a202 · outbound

This paper cites Secondpose: Se (3)- consistent dual-stream feature fusion for category-level pose estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Secondpose: Se (3)- consistent dual-stream feature fusion for category-level pose estimation

Reference 12

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 3c3f855c-4d18-4bf2-9097-29755fcae652 · outbound

This paper cites Masked-attention mask transformer for universal image segmentation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Masked-attention mask transformer for universal image segmentation

Reference 13

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Observation edacdb6c-00ae-4909-8dd4-2dcd354584f8 · outbound

This paper cites 3d pose esti- mation of daily objects using an rgb-d camera.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes 3d pose esti- mation of daily objects using an rgb-d camera

Reference 14

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Observation ec6a0122-e0f5-4e6b-86fd-6d3d6f86db96 · outbound

This paper cites Object level depth recon- struction for category level 6d object pose estimation from monocular rgb image.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Object level depth recon- struction for category level 6d object pose estimation from monocular rgb image

Reference 15

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Observation be1194df-87a7-44ca-bd3b-55d48b528af0 · outbound

This paper cites inemo: Incremental neural mesh models for robust class-incremental learning.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes inemo: Incremental neural mesh models for robust class-incremental learning

Reference 16

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Observation c1e85c55-daef-4ba4-af59-99b2995de673 · outbound

This paper cites Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography.Communications of the ACM, 24(6):381–395, 1981.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography.Communications of the ACM, 24(6):381–395, 1981

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6ae1df38-32ce-45a8-8353-1e4edaf58c1d · outbound

This paper cites Mask r-cnn.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Mask r-cnn

Reference 18

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Observation b14ea190-67fd-4437-b18d-66ab83888eb2 · outbound

This paper cites Pvn3d: A deep point-wise 3d keypoints voting network for 6dof pose estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Pvn3d: A deep point-wise 3d keypoints voting network for 6dof pose estimation

Reference 19

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation ae863c4d-bb9d-40e8-9ad9-fe606f8ff5b4 · outbound

This paper cites Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations

Reference 20

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Unavailable: canonical work link unavailable.

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Observation 35d0a333-c18d-4ed5-9edc-d58c2dcd5f66 · outbound

This paper cites A direct least- squares (dls) method for pnp.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes A direct least- squares (dls) method for pnp

Reference 21

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Observation 48cfacb6-cf30-469a-be98-4363b68be95e · outbound

This paper cites Segmentation-driven 6d object pose estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Segmentation-driven 6d object pose estimation

Reference 22

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f04b2083-0897-408a-bcbe-9cfc1f8c181d · outbound

This paper cites Single-stage 6d object pose estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Single-stage 6d object pose estimation

Reference 23

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Observation 7aba780c-59a6-4305-b7d2-cca1aba08de6 · outbound

This paper cites Centersnap: Single-shot multi-object 3d shape reconstruction and categorical 6d pose and size estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Centersnap: Single-shot multi-object 3d shape reconstruction and categorical 6d pose and size estimation

Reference 24

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7ca82dec-9b1c-4549-be78-8bdaeee6e5de · outbound

This paper cites Shapo: Im- plicit representations for multi-object shape, appearance, and pose optimization.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Shapo: Im- plicit representations for multi-object shape, appearance, and pose optimization

Reference 25

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 6036e50e-ed4a-4c10-9616-0aaa39ce5310 · outbound

This paper cites Novum: Neural object volumes for robust object classification.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Novum: Neural object volumes for robust object classification

Reference 26

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation fb49ae59-a21f-4c5a-8349-177797c9cf5d · outbound

This paper cites Real-time perception meets reactive motion gener- ation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Real-time perception meets reactive motion gener- ation

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 0912d48a-f95e-4c94-bf7b-2cb53c4f8d3c · outbound

This paper cites Pose estimation for an autonomous vehicle using monocular vision.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Pose estimation for an autonomous vehicle using monocular vision

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 3fb0955b-a1d7-4e60-aa10-dc1c4ba7c5a0 · outbound

This paper cites Cosypose: Consistent multi-view multi-object 6d pose estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Cosypose: Consistent multi-view multi-object 6d pose estimation

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.291800Z digest=sha256:ef5b0c4f8b29b2a93161ee0bd128e87f981ece10b565888a352b9df6130fbd03

Observation c6e2dd61-fe3f-4cd3-a34f-bf5d1f422ee6 · outbound

This paper cites Category-level metric scale object shape and pose estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Category-level metric scale object shape and pose estimation

Reference 30

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raw_fallback, observed 2026-08-06T05:14:37.840269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.310196Z digest=sha256:87b8924179d99576e33cb60e0a8955bae0d82b3a5e946b2ea4850ad276b8b237

Observation 439024e4-6f02-4946-a62a-091e9f91d287 · outbound

This paper cites Epnp: An accurate o(n) solution to the pnp problem.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Epnp: An accurate o(n) solution to the pnp problem

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.321434Z digest=sha256:cd22fa5b51404ec1f9e8399b5006f5ea455a5a9dcd619be6dc618fd579ae2e97

Observation 05ce3485-3cb3-4b13-9ea4-6d3fbd364711 · outbound

This paper cites Deepim: Deep iterative matching for 6d pose estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Deepim: Deep iterative matching for 6d pose estimation

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 82140d6a-8e06-4984-9e23-506b624f5098 · outbound

This paper cites Dualposenet: Category-level 6d object pose and size estimation using dual pose network with re- fined learning of pose consistency.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Dualposenet: Category-level 6d object pose and size estimation using dual pose network with re- fined learning of pose consistency

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.344351Z digest=sha256:40ffabd590d73f72d55663b35680a1f9c24577715a9e975e5ba85e2107e5c890

Observation ff9f01b0-91cd-4672-aec7-cebb06a0d0b8 · outbound

This paper cites Category-level 6d object pose and size estimation using self- supervised deep prior deformation networks.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Category-level 6d object pose and size estimation using self- supervised deep prior deformation networks

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.779259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.352762Z digest=sha256:cdadd0ce5c4a9f7483d902f8c39bd860894f78ea1acdf9ecc65e96d87696e8ae

Observation a62f121e-4f8a-4540-8785-4dc4fb9d34e6 · outbound

This paper cites Instance-adaptive and geometric-aware keypoint learning for category-level 6d object pose estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Instance-adaptive and geometric-aware keypoint learning for category-level 6d object pose estimation

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.766864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.358670Z digest=sha256:e887bc94063f5223f66946ad889a2b80bde6065971c3e736eb863d5883cc6c91

Observation 5a9f8396-ea46-4380-a4dd-396203bee834 · outbound

This paper cites Single-stage keypoint-based category-level object pose estimation from an rgb image.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Single-stage keypoint-based category-level object pose estimation from an rgb image

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.750131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.371520Z digest=sha256:269e8ed083bda6baeeeb11cc5caca6d1c7170583beb003267ba39e393457590b

Observation 5d93b3ac-1bf6-436b-8ad9-148b01758e7e · outbound

This paper cites Deep learning-based object pose estimation: A comprehensive survey.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Deep learning-based object pose estimation: A comprehensive survey

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T05:14:36.387455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:14:36.387455Z digest=sha256:944fbb4e296a94cab56b60efd6e72a18bd1f07cccbd7a516595c403c1b3bda17

Observation 122c2468-d0e0-48d7-8f1d-5ce562534233 · outbound

This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T05:14:36.411738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:14:36.411738Z digest=sha256:4887d35e7a84330dd5705c494a2d03337ec83deaf1dde0f0ab2d6e4a9dabf4b3

Observation 6bcd02f1-6886-48da-a1a4-1208c0c9e694 · outbound

This paper cites Decoupled Weight Decay Regularization.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Decoupled Weight Decay Regularization

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T05:14:36.417846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:14:36.417846Z digest=sha256:cda3270811d1876ad26bb24391e241c6c0b1176789fd56bcc46bbaa97da191ea

Observation 89b17b11-d027-4279-a1ee-184f799fe1f0 · outbound

This paper cites Robust category-level 6d pose estimation with coarse-to-fine rendering of neural features.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Robust category-level 6d pose estimation with coarse-to-fine rendering of neural features

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.734241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.423509Z digest=sha256:81f8407e8d943f6d60d884593da98592c3972ae1a99c0611b98ed4fcbc6bc12e

Observation 722534d4-f222-4be4-8f05-a1dd64d8c783 · outbound

This paper cites Pose estimation for augmented reality: a hands-on survey.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Pose estimation for augmented reality: a hands-on survey

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.715679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.447649Z digest=sha256:d7103ffa8b7000239bfbe921ef643a930efa51f2d70b3fa161324bc53a357a7d

Observation a90f30fb-ae4a-4f64-ba47-05a4f8c069bb · outbound

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

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes DINOv2: Learning Robust Visual Features without Supervision

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T05:14:36.452358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:14:36.452358Z digest=sha256:a0a2d4be54aa526a02ff0728484ef0f32503c5132d35a4f2d76b38ed9054eadd

Observation e205e8cd-7e98-473e-9c21-64628a69d9cd · outbound

This paper cites Accelerating 3D Deep Learning with PyTorch3D.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Accelerating 3D Deep Learning with PyTorch3D

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T05:14:36.465212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:14:36.465212Z digest=sha256:7bcc2511e660a03b7e001b7da0998542d6b13b67e3e7e542538e9b0e698b3c0b

Observation 2be4551c-7d46-423b-b18c-74fed62e382c · outbound

This paper cites Faster r-cnn: towards real-time object detection with re- gion proposal networks.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Faster r-cnn: towards real-time object detection with re- gion proposal networks

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.699338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.482230Z digest=sha256:9602ce467901846d106ceec2323d731c8bb67350af0761d1ce616329315d34d6

Observation 6b295475-2a27-4cb8-918f-026ae28161f9 · outbound

This paper cites Fast 3d recognition and pose using the viewpoint feature histogram.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Fast 3d recognition and pose using the viewpoint feature histogram

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.669346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.525844Z digest=sha256:7497a04d1590f984d2d6acc271ef1a6956629e05549416c9d0f70dd7da4c0d06

Observation 3667bca0-fc41-4d32-82ba-476041abeeed · outbound

This paper cites Deep multi-state object pose estimation for augmented reality assembly.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Deep multi-state object pose estimation for augmented reality assembly

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.650131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.557084Z digest=sha256:f4b0d011fd6f537cc1114ca25eed8c86a309b35ca604dc0474a5e3058c5e5b61

Observation c0746059-cabb-42fd-93a1-066cbac36b18 · outbound

This paper cites Zebrapose: Coarse to fine surface encod- ing for 6dof object pose estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Zebrapose: Coarse to fine surface encod- ing for 6dof object pose estimation

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.623242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.567539Z digest=sha256:5d7c9a3bb23e500d756d8452bd76e89b70852449651c3d6e23d12254fffa6016

Observation 28c5272a-cf09-492b-a567-a05a6fa62ac2 · outbound

This paper cites Generalised dice overlap as a deep learning loss function for highly unbalanced segmen- tations.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Generalised dice overlap as a deep learning loss function for highly unbalanced segmen- tations

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.604988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.585530Z digest=sha256:f960a793616f320b2f5432cdf7741566d1c3154960067918d3478d4d7c1f3e63

Observation f3e7ff66-82a8-49a1-8080-37d2d50ac5e4 · outbound

This paper cites Real-time seamless single shot 6d object pose prediction.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Real-time seamless single shot 6d object pose prediction

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.584677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.589806Z digest=sha256:c2d7d58ac85c99639e791e222c829b1237bbb8190caeed16dfae21e710a952e7

Observation 703b647e-2134-45d2-82d0-5291aa9307aa · outbound

This paper cites Cope: End-to-end trainable constant runtime object pose es- timation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Cope: End-to-end trainable constant runtime object pose es- timation

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.568397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.601605Z digest=sha256:dcb714238085b54de5959908cf5b5e6ee98bed0d2e222f2b81fa8cb000246cfd

Observation 92c24449-a9e0-4ed4-b3c7-9cb6ef7e406a · outbound

This paper cites Shape prior deformation for categorical 6d object pose and size estima- tion.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Shape prior deformation for categorical 6d object pose and size estima- tion

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.550691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.634752Z digest=sha256:ef91fc34e37796182e5bc1b9353216da8455fdfccdc37ae3a6def8d63e6db965

Observation 3ff31475-a969-4c42-9020-747ad85b19d7 · outbound

This paper cites Least-squares estimation of transforma- tion parameters between two point patterns.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Least-squares estimation of transforma- tion parameters between two point patterns

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.532424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.670140Z digest=sha256:3ea9dd8aef2eff1ea8ebb65feb60ae0bd591045bf4ea91c628ccbb5abb52c055

Observation 58a9f650-7c16-4a83-aaca-abab3e23d1c2 · outbound

This paper cites Socs: Semantically- aware object coordinate space for category-level 6d object pose estimation under large shape variations.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Socs: Semantically- aware object coordinate space for category-level 6d object pose estimation under large shape variations

Reference 53

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no resolver link, observed 2026-08-06T05:14:36.674346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:14:36.674346Z digest=sha256:e493a974aabfb52be16972af1cae279efb9cb0863988a478ecbb92d7fb290dd7

Observation e8c7b280-463a-4feb-b476-cf9b6dc330a4 · outbound

This paper cites Normalized object coordinate space for category-level 6d object pose and size estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Normalized object coordinate space for category-level 6d object pose and size estimation

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.509178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.695470Z digest=sha256:233d6b4ea9ef99feee018d500851b0f1a40d942fd2a67eb5462677ee563c1756

Observation 23408fef-1559-4ab7-9ae1-b45238e9978e · outbound

This paper cites Rgb-based category-level object pose estimation via decoupled metric scale recovery.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Rgb-based category-level object pose estimation via decoupled metric scale recovery

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.484821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.728290Z digest=sha256:08e9b36e3bfdda23868a911877f92ae8be82fb33c9e48505359852a09bd950ea

Observation 798bc57e-8c6d-4f2c-be3a-86ae0ba6baf1 · outbound

This paper cites Catgrasp: Learning category-level task-relevant grasping in clutter from simulation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Catgrasp: Learning category-level task-relevant grasping in clutter from simulation

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.447691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.745347Z digest=sha256:09879a785a991c42890067ee4ac1ff1bd355e09dcab50093e6eaecb20b6b7738

Observation 36b032ab-ecbb-4e88-85a6-5ec5d65bd48c · outbound

This paper cites You Only Demonstrate Once: Category-Level Manipulation from Single Visual Demonstration.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes You Only Demonstrate Once: Category-Level Manipulation from Single Visual Demonstration

Reference 57

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unresolved
no resolver link, observed 2026-08-06T05:14:36.766257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:14:36.766257Z digest=sha256:818a88c5f45f54b2f3e1204e7c699358fbab80b38ef5d8ee146470b5df4c9d2c

Observation 16fb049a-4e5e-4fa5-812b-32626e542141 · outbound

This paper cites PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

Reference 58

Resolution
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no resolver link, observed 2026-08-06T05:14:36.778077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:14:36.778077Z digest=sha256:4998fbe9f7fb3a8e6d158722a698252ad64abd18964ff7382625d822de197818

Observation e76fc565-f916-479d-85eb-671aad57e750 · outbound

This paper cites Parameter-efficient fine-tuning for pre-trained vision models: A survey.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Parameter-efficient fine-tuning for pre-trained vision models: A survey

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-06T05:14:36.815867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:14:36.815867Z digest=sha256:45efe095a02def270db0163804d0466875e1476224292ae72cbe8d9ca8ee628b

Observation a33b92a3-169b-4e15-9832-ce0f6c929d0a · outbound

This paper cites Dpod: 6d pose object detector and refiner.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Dpod: 6d pose object detector and refiner

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.436457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.856605Z digest=sha256:748b70c81c1ef9d04eba47934f04c60e3b3577f55e555e028e4146c51891e859

Observation 3692bd2b-1580-4f99-b545-8dd2ad8175ee · outbound

This paper cites Genpose: gen- erative category-level object pose estimation via diffusion models.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Genpose: gen- erative category-level object pose estimation via diffusion models

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.422976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.902840Z digest=sha256:641e77f7d8216f119c17af3e41214add2733927e9c95f78bf070243f8e4e29c6

Observation ecab0dd0-6e4c-4ce2-a3c0-b7672f8e1d00 · outbound

This paper cites Lapose: Laplacian mixture shape modeling for rgb-based category-level object pose estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Lapose: Laplacian mixture shape modeling for rgb-based category-level object pose estimation

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.410960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.934845Z digest=sha256:ef9718245cedd92124b132eca7671a776899fc18c31e3f0b34c405e7a6ce2e23

Observation 52a47274-130b-4221-ada8-a6ec9f827900 · outbound

This paper cites Deep fusion transformer network with weighted vector-wise keypoints voting for robust 6d object pose estimation.

Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes Deep fusion transformer network with weighted vector-wise keypoints voting for robust 6d object pose estimation

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.397402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:14:36.973376Z digest=sha256:3fea9c6eafc22ad830c214d32d573fce99d7f3554ce6164752870292436b203c

Pith citing papers

No inbound Pith citation observations are available.