Pith. sign in

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 2026-08-07T06:34:17.273281+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

  • verified exact0
  • verified fuzzy49
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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

Resolution
unresolved
no resolver link, observed 2026-08-06T05:14:35.096273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:14:35.096273Z digest=sha256:d224167ac23e1b0ab1689816e67da121be2362fe1de87b126ae8957636a02b11

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:38.182798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:35.178425Z digest=sha256:7309a2400c6baa8b92cd415c01d5f802c8b0f146204e7977635514a7a824963a

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:38.171045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:35.284383Z digest=sha256:7efef8793bfedd7a86d71d0b3de6fd75efb65f4e33a2a8395c44336f48bd4ecf

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:38.158608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:35.355230Z digest=sha256:6205baf271bb207d3f3b630bd3dae710f95c2b923eb0c917e9ed65b60404d41a

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:38.146759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:35.456859Z digest=sha256:a96f8b877306b7582cffadc1ac989a5da3692d98d72697636c0c507bbcba8dcd

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:38.135006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:35.565507Z digest=sha256:139357be34edec393d029a3adb11f47c3a27511686e3c6089debc96eec86c044

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

Resolution
unresolved
no resolver link, observed 2026-08-06T05:14:35.690987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:14:35.690987Z digest=sha256:c1f0b6135879f6a736dcd5f9a45b8545c35395383f2dbaf7d86d09ee883fc877

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

Resolution
unresolved
no resolver link, observed 2026-08-06T05:14:35.821269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:14:35.821269Z digest=sha256:9afbd6734d1345321da47267ee868a5d47dfdee3b2b01287b00c42736961a9bf

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:38.109125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:35.961011Z digest=sha256:257b574c52f0f2c5a855cd671972d874a79b9ae50b2f1bb04190f9e724e70978

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:38.093762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:35.985530Z digest=sha256:bc24368bb6ea14dd421844b0e4c678437cc6e0d129945e64754837e7d8a63703

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:38.074472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.005103Z digest=sha256:58dfbd8a3465711fc045220387e8f36b813d5ffeb52709cea899b86b2ad4ddee

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:38.060576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.019910Z digest=sha256:209a6458dddf3c2d0c0c85fe894eb8230b54d23328b48cacb32ac8f65feefbbc

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:38.048614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.029335Z digest=sha256:d4f64b1dbca00fd4f74ddd8ee022133fc1c07146f77015c4b5c3304f78f9789f

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:38.034093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.037030Z digest=sha256:e24ead030d6665386b78411149b9592729864ef5c716467cc83dcd2e879bc4b3

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:38.019265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.053551Z digest=sha256:4586d7c5d990f5b935e84a2c0c9da6daa444dd0e46b5160ee903a3634d287471

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:38.006393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.076725Z digest=sha256:d7bc621b75e04449da8d6ccaec952601becfc50a5d6d7581bb0af699daa47423

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

Resolution
unresolved
no resolver link, observed 2026-08-06T05:14:36.090710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:14:36.090710Z digest=sha256:ce463c838db406bb6cd195cda87bcca2c1a368f8bc4b4d58aae0eaae7ede1b95

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.986230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.103282Z digest=sha256:ab06225ca5e8d62ace31e3ceafcfa32b8ca6a6da40980b97afa75e5b0fb0f1aa

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.972446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.113943Z digest=sha256:3a843cfad21c317885b4526e2d491e098f35f2c187bc855886e18249563a98e8

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

Resolution
unresolved
no resolver link, observed 2026-08-06T05:14:36.150490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:14:36.150490Z digest=sha256:eff58de1fe583e03fea841392ff8e9f098ce7a81553d951c46888d8e21843d05

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.953132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.175802Z digest=sha256:7d64ba825afd4f28ce4f34e2a7731678def3329f4a27b81c7df0aa3b984aa3b2

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.938222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.204379Z digest=sha256:89263fed4dcd1c90eea8be0e6a041f1fb84ed7fb04417cc02c1c9b1fbdaa2ec1

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.926266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.220037Z digest=sha256:b4395eb3d84e678d78afb88bb2094f0a55ba3ec55d6118f16936a8407ba1a371

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.915484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.230151Z digest=sha256:fce1b377b1b7c8959786cf25a18411943b116617c9e85c0fb0e689dbb512d16d

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.902815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.239071Z digest=sha256:b7afcefc0146c95845a08a01d90611659dc60aadde4d94048088fedb4d6568b6

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.892103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.248466Z digest=sha256:bcbeb25183a47dadb14a61fc0b71b7a1389c5038ba1cd7761ea8501312590d01

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.879618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.256214Z digest=sha256:9d1528705babbd88ae7f9a9d8dbc95643020ee66efb2b816bde854f8d89c2c73

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.866535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.269241Z digest=sha256:15c0ed55f8da21cfc8fd6250b16cdd1a8e63bad405d55ff8380f480855c58f6c

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.852360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.291800Z digest=sha256:b4c8412d0e1f58756a422b17f0c91737a8a54fb8bc3bb1810fcf3fbfe390b93f

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

Resolution
verified fuzzy
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.310196Z digest=sha256:d35c691a4f97dd3085c9b60f76d3fdcf6509d81f05d6edcae4d9669bc7215f77

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.821908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.321434Z digest=sha256:ceccde9d56b6ee6604a4ecb7ae5c3f645fad9d9293a46fcd17824b6408281985

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.806006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.337582Z digest=sha256:5a287b14a19371828c9db7ab10c6af01c133137e085eaee6e8d559ba97b59ce2

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:14:37.792477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.344351Z digest=sha256:5d1f79d6a8c0284422ed6db12969277c814d88c7a7b3a59657fcc82334f0c427

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

Resolution
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.352762Z digest=sha256:0bb9b831007473a1d0591aeb52c1a86e34e97a1350b783704b99ccafd6ad5d0a

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.358670Z digest=sha256:53a8cc21b3b3f208f4ab6539405f028f50b8afe56e5733cfa5f59c7e8fbeae14

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.371520Z digest=sha256:64cd66ed752b48242429c8488541ab045832653dee45f44dca9c7b3fa71e818a

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.423509Z digest=sha256:daad5294396c1b77a975a1a7075c5a40a5eb4bb9ca052442cdc583b86a05e324

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.447649Z digest=sha256:fe7181d26696eec6f47478b64552fca6787ff1bd2a75ea5e5fa43b92e297f0bc

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.482230Z digest=sha256:67893a6d94cb02cfaf9f42e3f9cb7e47fafd5123baa1d0e1919a0be6d025b212

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.525844Z digest=sha256:0468433bdc18ab78b06a92a9021e04ede423ecf2fbfc01f9bd7aab31b674a654

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.557084Z digest=sha256:a5aa4634badd9a9e173ba6479edeb9daa8d8bd7b81a808111960a7c8e11ed293

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.567539Z digest=sha256:61a650a98a4618352031e0f56abeaa81d77e7479c83202c2bd52756453a2659f

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.585530Z digest=sha256:049481b72d94debf9614383ab33507353606e985ac81486826d7b1a1fa81b2cf

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.589806Z digest=sha256:b37e1adc221aa221771b3a8a872d2aafb136f50845be21d0fb14f103988b4b73

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.601605Z digest=sha256:957ab6f84ee4d5650dbf0556d3ac84e7b0c67b4d4cf04269956eeedaf7da59da

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.634752Z digest=sha256:336292b30327e7478f2516bce58add936c833061d610fe14a9acfc03d375be5f

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.670140Z digest=sha256:70e03449e584257fd4f96308efe6bb029cd3fedd35627b7205bc6664a1939d57

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

Resolution
unresolved
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.695470Z digest=sha256:6bd1abfe2abba28825509043a0757cad27e1d583e78e43bcefd09a4bbda1145a

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.728290Z digest=sha256:ff4ca9461e250729885ee09aa7a9859d3c59e34b2b94e22661fa1bcb96815f19

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.745347Z digest=sha256:b7f601cd60922cce7a58b310faba34c9a66ef09ded417d8bbb5894634db0e4ec

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

Resolution
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
unresolved
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.856605Z digest=sha256:ebeba449fdcaf6f50740e41f0c498c0085a038d09112059208c973e9812b4456

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.902840Z digest=sha256:ce9f62633539e8d9fc4dd1f6e0c4f43d58d8a7535b24c22f152c084930153561

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.934845Z digest=sha256:ca2263846c0fdcb7538b858d0658354d1f2d9cea9e2c6fd7ff22ee44cc42ac3e

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T05:14:36.973376Z digest=sha256:1357260942a27aa9199b7f72999864f687b5e1f50f5d48c81034d8f3b92e0256

Pith citing papers

No inbound Pith citation observations are available.