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Paper Citation Record · LEDGER

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation

As of 8 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 0 inbound Pith citation observations for arXiv:2505.17475.

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

pith.paper-citation-record.v1
2505.17475 v1

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:51:46.600152Z

measured 70 of 70 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

70 of 70 outbound references displayed

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  • verified fuzzy64
  • unresolved6
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4d066b07-21e1-4de5-88f0-631d1b905847 · outbound

This paper cites 2D human pose estimation: New benchmark and state of the art analysis.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation 2D human pose estimation: New benchmark and state of the art analysis

Reference 1

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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 7e5f73ac-d410-4a3d-8f1a-7d8d5e4f4e4d · outbound

This paper cites PoseTrack: A benchmark for human pose estima- tion and tracking.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation PoseTrack: A benchmark for human pose estima- tion and tracking

Reference 2

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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 85708d10-2ce0-44b3-9ad9-5984004395e3 · outbound

This paper cites This looks like that: Deep learn- ing for interpretable image recognition.Advances in Neural Information Processing Systems (NeurIPS), 32, 2019.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation This looks like that: Deep learn- ing for interpretable image recognition.Advances in Neural Information Processing Systems (NeurIPS), 32, 2019

Reference 3

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Source-reported events for the cited work

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Observation 3c339672-c8f1-4c3b-aa0b-fd8cb58e985d · outbound

This paper cites ScaleDet: A scalable multi-dataset object detector.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation ScaleDet: A scalable multi-dataset object detector

Reference 4

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:51:39.956999Z digest=sha256:1c0c935fbde38feed69110b674c798a028d729b0fb910883b51106e773df9b47

Observation 2442ff3b-8e13-450a-b1de-c0544afe3a47 · outbound

This paper cites Learning to estimate robust 3D human mesh from in-the-wild crowded scenes.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Learning to estimate robust 3D human mesh from in-the-wild crowded scenes

Reference 5

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Source-reported events for the cited work

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

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Observation 63d4bc59-613f-4d77-9175-978f557d1428 · outbound

This paper cites UniHCP: A unified model for human-centric perceptions.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation UniHCP: A unified model for human-centric perceptions

Reference 6

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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 1644e4eb-86c1-4359-b6e8-a345715f32ca · outbound

This paper cites Where are we with human pose estimation in real- world surveillance? InIEEE/CVF Winter Conference on Ap- plications of Computer Vision, pages 591–601, 2022.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Where are we with human pose estimation in real- world surveillance? InIEEE/CVF Winter Conference on Ap- plications of Computer Vision, pages 591–601, 2022

Reference 7

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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 1174735d-8e62-4087-88cb-3a5df33e53fd · outbound

This paper cites Weakly-supervised domain adaptive semantic segmentation with prototypical contrastive learning.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Weakly-supervised domain adaptive semantic segmentation with prototypical contrastive learning

Reference 8

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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 d137aca1-2d3e-4248-ab8f-1a0d3cbf8865 · outbound

This paper cites De- formable protopnet: An interpretable image classifier using deformable prototypes.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation De- formable protopnet: An interpretable image classifier using deformable prototypes

Reference 9

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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 12526150-a828-427e-9165-40b535a18f35 · outbound

This paper cites Weakly supervised semantic segmentation by pixel-to-prototype contrast.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Weakly supervised semantic segmentation by pixel-to-prototype contrast

Reference 10

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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 33220daf-9d8d-4e81-8929-829eb9cf5fdb · outbound

This paper cites Sigmoid- weighted linear units for neural network function approxima- tion in reinforcement learning.Neural networks, 107:3–11,.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Sigmoid- weighted linear units for neural network function approxima- tion in reinforcement learning.Neural networks, 107:3–11,

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:51:40.789893Z digest=sha256:c5b4f647ec829f0150e6b1271666c5736ad9acebc5b8653dc79e73cfca495c9b

Observation cb483565-b078-4e49-9854-ad9e55de8c3c · outbound

This paper cites Human pose as compositional tokens.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Human pose as compositional tokens

Reference 12

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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 96c785cb-c4d7-4167-87f0-9f8cec9e07f0 · outbound

This paper cites Human POSEitioning System (HPS): 3D human pose estimation and self-localization in large scenes from body-mounted sensors.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Human POSEitioning System (HPS): 3D human pose estimation and self-localization in large scenes from body-mounted sensors

Reference 13

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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=2026-08-07T14:51:41.044957Z digest=sha256:a5fc10eff84c60b2730412ed0de1002a8269b160aceab3ee6bb888b1f338775a

Observation 194fa52d-6e4a-4ea9-a175-bd991b2d7ae9 · outbound

This paper cites A graph-based approach for category-agnostic pose estimation, 2024.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation A graph-based approach for category-agnostic pose estimation, 2024

Reference 14

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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=2026-08-07T14:51:41.177409Z digest=sha256:c522bc62e5c7ddeedfbd70215338488339ff27f4f805fd80398df01760768ec9

Observation cb871251-2b69-4f09-aa0a-71840a21034d · outbound

This paper cites NeuMan: Neural human radiance field from a single video.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation NeuMan: Neural human radiance field from a single video

Reference 15

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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 c4346fb9-3b39-4f89-85b9-a663ec58c9aa · outbound

This paper cites MAS: Multi-view ancestral sampling for 3D mo- tion generation using 2D diffusion.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation MAS: Multi-view ancestral sampling for 3D mo- tion generation using 2D diffusion

Reference 16

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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 4134d363-e3ab-498e-ad66-b05f272d8a05 · outbound

This paper cites Sapiens: Foundation for Human Vision Models.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Sapiens: Foundation for Human Vision Models

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 85fe6f3a-7462-4fd9-8f05-dbbfba93440c · outbound

This paper cites Huang, Otmar Hilliges, and Michael J.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Huang, Otmar Hilliges, and Michael J

Reference 18

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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 9be360f9-7162-43eb-9a3f-fb98ca05cfba · outbound

This paper cites Human pose estimation for mitigating false negatives in weapon detection in video-surveillance.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Human pose estimation for mitigating false negatives in weapon detection in video-surveillance

Reference 19

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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 939ec3aa-341d-4fe5-bdb9-b91f980aa940 · outbound

This paper cites MSeg: A composite dataset for multi- domain semantic segmentation.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation MSeg: A composite dataset for multi- domain semantic segmentation

Reference 20

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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 289bbe13-92e3-458c-a099-97f8b546ae99 · outbound

This paper cites JRDB-PanoTrack: An open-world panoptic segmentation and tracking robotic dataset in crowded human environments.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation JRDB-PanoTrack: An open-world panoptic segmentation and tracking robotic dataset in crowded human environments

Reference 21

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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 a25c2d5f-4cb0-40fc-8135-6e80add3e8c6 · outbound

This paper cites SimCC: A simple coordinate classification perspective for human pose estimation.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation SimCC: A simple coordinate classification perspective for human pose estimation

Reference 22

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raw_fallback, observed 2026-08-07T14:51:54.965910Z

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 557af053-a04c-4590-9b4d-c7307198d336 · outbound

This paper cites Motion-X: A large- scale 3D expressive whole-body human motion dataset.Ad- vances in Neural Information Processing Systems (NeurIPS),.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Motion-X: A large- scale 3D expressive whole-body human motion dataset.Ad- vances in Neural Information Processing Systems (NeurIPS),

Reference 23

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raw_fallback, observed 2026-08-07T14:51:54.825679Z

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 7f277f56-3b65-42da-8011-ef6de0b05f6c · outbound

This paper cites Microsoft COCO: Common objects in context.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Microsoft COCO: Common objects in context

Reference 24

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raw_fallback, observed 2026-08-07T14:51:54.666851Z

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=2026-08-07T14:51:42.272802Z digest=sha256:f9ccf6c3f8f52ae74cbc5ab8b1d2c25120cf6b186d8318ce6047522b1a779943

Observation e7e19b31-6965-44af-b32e-d57332bc8dcf · outbound

This paper cites Learning orthogonal pro- totypes for generalized few-shot semantic segmentation.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Learning orthogonal pro- totypes for generalized few-shot semantic segmentation

Reference 25

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raw_fallback, observed 2026-08-07T14:51:54.515287Z

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 d72ddda4-6ea3-4200-bdcd-b1530739bc08 · outbound

This paper cites HumanGaus- sian: Text-driven 3D human generation with gaussian splat- ting.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation HumanGaus- sian: Text-driven 3D human generation with gaussian splat- ting

Reference 26

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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 7618a2bc-79dd-4ca7-a6a0-8578c222d08f · outbound

This paper cites an unresolved cited work.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Unresolved cited work

Reference 27

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raw_fallback, observed 2026-08-07T14:51:54.119086Z

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 13777d3f-20cf-447c-adaf-852b5123d189 · outbound

This paper cites ProMotion: Prototypes as motion learners.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation ProMotion: Prototypes as motion learners

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.

source=pdf_text observed=2026-08-07T14:51:42.734150Z digest=sha256:f761cc65548d2ed0c793bc9d70282d5cf1b2ab1bb26657e3d2cd443c925e3158

Observation 230d072d-2153-434a-bbf5-051248c4e36d · outbound

This paper cites InterHand2.6M: A dataset and baseline for 3D interacting hand pose estimation from a single rgb im- age.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation InterHand2.6M: A dataset and baseline for 3D interacting hand pose estimation from a single rgb im- age

Reference 29

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raw_fallback, observed 2026-08-07T14:51:53.761921Z

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 811c9070-ff31-4c28-84a7-f06c368dc2c5 · outbound

This paper cites Neu- ralAnnot: Neural annotator for 3D human mesh training sets.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Neu- ralAnnot: Neural annotator for 3D human mesh training sets

Reference 30

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raw_fallback, observed 2026-08-07T14:51:53.594895Z

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=2026-08-07T14:51:42.925826Z digest=sha256:cc04cdd344db9a8d248ee19510677e3052de6a49543d28efb876357ec5224735

Observation 12996112-a913-4434-aa06-44df55db19dc · outbound

This paper cites Three Recipes for Better 3D Pseudo- GTs of 3D Human Mesh Estimation in the Wild.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Three Recipes for Better 3D Pseudo- GTs of 3D Human Mesh Estimation in the Wild

Reference 31

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raw_fallback, observed 2026-08-07T14:51:53.378290Z

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=2026-08-07T14:51:43.023077Z digest=sha256:9460522b6e9feb36e4eefcbd5d49094b064c18a7159b39e81b41fbc4105d800b

Observation 6b8d9af0-68d7-4efe-8ed1-6637453a6859 · outbound

This paper cites Expressive whole-body 3D gaussian avatar.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Expressive whole-body 3D gaussian avatar

Reference 32

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raw_fallback, observed 2026-08-07T14:51:53.235757Z

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=2026-08-07T14:51:43.095619Z digest=sha256:e09717e5d65ac43dfd1125c7a9b8bda2dffae1c14245fa9bd35f23e3bd94c345

Observation 55db156e-4f6a-4b62-971c-d931d5a2a88e · outbound

This paper cites TranSG: Transformer- based skeleton graph prototype contrastive learning with structure-trajectory prompted reconstruction for person re- identification.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation TranSG: Transformer- based skeleton graph prototype contrastive learning with structure-trajectory prompted reconstruction for person re- identification

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-07T14:51:53.107549Z

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=2026-08-07T14:51:43.201085Z digest=sha256:6633ce6aaee5588a9398a11fafdc84d2f6b7415a0dbb30cda9175e85e6ac1061

Observation 49a95dd8-4488-4c3c-8b44-84e829e7453e · outbound

This paper cites an unresolved cited work.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:51:52.950249Z

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=2026-08-07T14:51:43.316627Z digest=sha256:c5072920a67805958f04f7bd47f3a33eb722b865fa4729dcf9965729e6c23808

Observation 3a6a5f44-de66-49d8-bd57-0f017c8884cd · outbound

This paper cites an unresolved cited work.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:51:52.803132Z

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=2026-08-07T14:51:43.383017Z digest=sha256:63e2bc0f3ac0aced0189d7b4eb3b7779c0326c119a4a2cb45560142d121f865b

Observation f9d9fe81-1b17-4399-8069-448d142b3047 · outbound

This paper cites Non- isotropy regularization for proxy-based deep metric learning.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Non- isotropy regularization for proxy-based deep metric learning

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:52.652939Z

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=2026-08-07T14:51:43.452606Z digest=sha256:f63011253a066f00a10912a3aeff79edef7b1bdac9287b9a161dbf50cf6a4917

Observation bc3c53f8-5a17-45ab-a95a-b770b50f0834 · outbound

This paper cites Learning 3D human pose estimation from dozens of datasets using a geometry-aware autoencoder to bridge between skeleton formats.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Learning 3D human pose estimation from dozens of datasets using a geometry-aware autoencoder to bridge between skeleton formats

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:52.506170Z

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=2026-08-07T14:51:43.520032Z digest=sha256:77288bd2346b68824bb07667439ce35699b53e13d2688a7d2e88c1f12f09723f

Observation 75cf168b-75a5-4484-95b4-4263f7bd066e · outbound

This paper cites Common Pets in 3D: Dynamic new-view synthesis of real-life deformable categories.IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Common Pets in 3D: Dynamic new-view synthesis of real-life deformable categories.IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:52.398479Z

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=2026-08-07T14:51:43.609778Z digest=sha256:74c602fc1bab085622d85cdc00821481736ee58c5f177036b2fd01835d71c5e7

Observation 1abf4024-bfbf-450b-9e07-6b9026193414 · outbound

This paper cites Concerning nonnegative matrices and doubly stochastic matrics.Pacific Journal of Mathematics, 21(2):343–348, 1967.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Concerning nonnegative matrices and doubly stochastic matrics.Pacific Journal of Mathematics, 21(2):343–348, 1967

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:52.156619Z

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=2026-08-07T14:51:43.703787Z digest=sha256:deadef786c92ce9ead4e5578647e09ae3ba7bd37ff58e3ecf42215cfd9e4df37

Observation 6e896af6-6008-4c1b-9376-0e85d7b6efd9 · outbound

This paper cites Prototypical networks for few-shot learning.Advances in Neural Infor- mation Processing Systems (NeurIPS), 30, 2017.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Prototypical networks for few-shot learning.Advances in Neural Infor- mation Processing Systems (NeurIPS), 30, 2017

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:51.917809Z

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=2026-08-07T14:51:43.761876Z digest=sha256:da825f08721893832705997a02995d586641e763dda5dfa12426e5ea29b4d9f6

Observation 0d0d0ee8-d658-40d3-b600-b6e90b4a64b9 · outbound

This paper cites Vision-based fallen person detection for the elderly.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Vision-based fallen person detection for the elderly

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:51.654172Z

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=2026-08-07T14:51:43.836418Z digest=sha256:a3ffddd7d854a1fd45a43c6dcfb011aaaa95f1f558e5ee2d8a281e3f79c27407

Observation 1b363903-101b-46a9-b54a-4577fc728123 · outbound

This paper cites Deep high-resolution representation learning for human pose esti- mation.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Deep high-resolution representation learning for human pose esti- mation

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:51.460509Z

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=2026-08-07T14:51:43.927222Z digest=sha256:841ccabcf8fca610b65ad112688833f51a9aa1d9715d7386c3f0e746c1bd126f

Observation b3802789-15e9-45b5-832a-8210c478234e · outbound

This paper cites Monocular, one-stage, regression of multiple 3D people.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Monocular, one-stage, regression of multiple 3D people

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:51.348803Z

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=2026-08-07T14:51:43.994661Z digest=sha256:e4992d412e4a9bce235c9b272018595846f57ccc7b9864761813a39b3c5d4bc2

Observation bf3a4427-4d96-4c4f-9013-53bd05601a30 · outbound

This paper cites Putting people in their place: Monocular regression of 3D people in depth.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Putting people in their place: Monocular regression of 3D people in depth

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:51.214837Z

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=2026-08-07T14:51:44.073805Z digest=sha256:990f1b2b093826f5472cb36da2f7ac11e22604105a3ce27cef61e776ae9c8c91

Observation 9da98c12-89d6-497d-b039-98fce7b9bc9b · outbound

This paper cites xR-EgoPose: Egocentric 3D human pose from an hmd camera.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation xR-EgoPose: Egocentric 3D human pose from an hmd camera

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:50.996332Z

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=2026-08-07T14:51:44.127701Z digest=sha256:265f943f51d090cdf2953c43931282d52e3cfa7924dff3192ccc3683279c419c

Observation e3b4cd36-e23d-48ed-8f00-b50b29b3863f · outbound

This paper cites JRDB-Pose: A large-scale dataset for multi- person pose estimation and tracking.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation JRDB-Pose: A large-scale dataset for multi- person pose estimation and tracking

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:50.714961Z

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=2026-08-07T14:51:44.206398Z digest=sha256:3919f7ae8faa4f3a28591352fdbc36e3e83103a0c3903f6f5b6c9b4759a7cebc

Observation 1a65c6d2-0f30-4232-955f-aaf073f402b1 · outbound

This paper cites Recovering accurate 3D human pose in the wild using imus and a moving camera.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Recovering accurate 3D human pose in the wild using imus and a moving camera

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:50.499709Z

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=2026-08-07T14:51:44.328882Z digest=sha256:7197625a8918185082d267df683baa996145bc70149577dc9044454a6653bbf3

Observation c5a1473a-ee67-48f3-8979-539e7823ee72 · outbound

This paper cites Learning support and trivial prototypes for interpretable im- age classification.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Learning support and trivial prototypes for interpretable im- age classification

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:50.300137Z

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=2026-08-07T14:51:44.414840Z digest=sha256:632ad851f27d61b48e724a33f5bc77c34124478ae01236fd8602244d5f08d5b2

Observation c1e9b7ba-c5ec-4390-8746-4cf09648bbfb · outbound

This paper cites Scene-aware ego- centric 3D human pose estimation.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Scene-aware ego- centric 3D human pose estimation

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:50.125149Z

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=2026-08-07T14:51:44.502890Z digest=sha256:eb72d5cc1c87895b0cf2647a9b172f8281a1500c46500d2793f7af90a41307ad

Observation 7a0edd29-e977-4736-af71-35aba116f2f6 · outbound

This paper cites Towards universal object detection by domain at- tention.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Towards universal object detection by domain at- tention

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:49.958331Z

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=2026-08-07T14:51:44.575432Z digest=sha256:c13073c78d1d40857a42e5e52a3287a4757091cbf42c2e592984ea0b531cf804

Observation 7c62f92e-b032-43bf-8da1-7f2f5a30d907 · outbound

This paper cites Do different tracking tasks require different appearance models?Advances in Neu- ral Information Processing Systems (NeurIPS), 34:726–738,.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Do different tracking tasks require different appearance models?Advances in Neu- ral Information Processing Systems (NeurIPS), 34:726–738,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:49.807178Z

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=2026-08-07T14:51:44.685026Z digest=sha256:8544de713667c974468dada982011529733d77bd6594fa66a7be018b28172c86

Observation b8caa70e-0b3a-4d93-9cd8-487d67aa1f56 · outbound

This paper cites AI Challenger : A Large-scale Dataset for Going Deeper in Image Understanding.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation AI Challenger : A Large-scale Dataset for Going Deeper in Image Understanding

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T14:51:44.766602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:51:44.766602Z digest=sha256:747e135fb36b95a0c682f446e2c2a0338624e8f58c987932cdef071456cc0a5c

Observation 5aeeac70-509d-4f17-a553-00525f871947 · outbound

This paper cites Simple baselines for human pose estimation and tracking.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Simple baselines for human pose estimation and tracking

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:49.624480Z

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=2026-08-07T14:51:44.850513Z digest=sha256:7cfe2014b151102f70216268ce46cecf67698331348dc7495d04a6620424fa93

Observation b8d8a3cd-b88b-4a7b-be6c-cc963c334384 · outbound

This paper cites Universal-RCNN: Universal object detector via transferable graph r-cnn.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Universal-RCNN: Universal object detector via transferable graph r-cnn

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:49.447821Z

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=2026-08-07T14:51:44.913889Z digest=sha256:f40ca087a972dcdbb57c6480eed331d5fb5ef489997ec343f4218053dbb0cdaf

Observation fb591f5c-1b6a-4542-b950-ea293a57d298 · outbound

This paper cites Pose for ev- erything: Towards category-agnostic pose estimation.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Pose for ev- erything: Towards category-agnostic pose estimation

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:49.252451Z

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=2026-08-07T14:51:45.026668Z digest=sha256:b2a1963cc39a7ec9855ec6ebf4fc32aebe46d21e26c3588338f49717bdc55a77

Observation 55e52d3c-ae78-4c34-a5cd-86c9ec4caf4f · outbound

This paper cites ViTPose++: Vision transformer for generic body pose esti- mation.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation ViTPose++: Vision transformer for generic body pose esti- mation.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:49.085815Z

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=2026-08-07T14:51:45.155467Z digest=sha256:b2ec5030379f2e1485731c3331452256e66bab0a8a2f9b76f87875f00097a5e6

Observation 7acd70b0-12ef-4504-a768-6f4e1fc417d5 · outbound

This paper cites ScoreHypo: Probabilistic human mesh estimation with hypothesis scoring.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation ScoreHypo: Probabilistic human mesh estimation with hypothesis scoring

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:48.927764Z

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=2026-08-07T14:51:45.281304Z digest=sha256:f5827c45fec04055106a672379767e77d6ef6e210581388b24b0d93b9aa19f7b

Observation 9a881327-9025-4723-9073-297f9b25472f · outbound

This paper cites UNIK: A unified framework for real-world skeleton-based action recognition.British Machine Visison Conference (BMVC),.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation UNIK: A unified framework for real-world skeleton-based action recognition.British Machine Visison Conference (BMVC),

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:48.810459Z

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=2026-08-07T14:51:45.436020Z digest=sha256:8adc5ba0b454a46bc277ded5538bab2c29d32e81676e02c7058398c9e7463c5e

Observation 85de67af-e5a0-4108-b94e-7c080b47d98c · outbound

This paper cites KITRO: Re- fining human mesh by 2D clues and kinematic-tree rotation.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation KITRO: Re- fining human mesh by 2D clues and kinematic-tree rotation

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:48.696901Z

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=2026-08-07T14:51:45.558818Z digest=sha256:795c3d8be8882056b6d49a2147f55f5d4819dde4801f99eec397d0869af15577

Observation 2d42f581-200b-4c36-a3ff-5ede8b26d07d · outbound

This paper cites APT-36K: A large-scale benchmark for animal pose estimation and tracking.Advances in Neural In- formation Processing Systems (NeurIPS), 35:17301–17313,.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation APT-36K: A large-scale benchmark for animal pose estimation and tracking.Advances in Neural In- formation Processing Systems (NeurIPS), 35:17301–17313,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:48.544403Z

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=2026-08-07T14:51:45.720827Z digest=sha256:1d6cc349de27690d48ccb2ecf447200fd7cd5dfc55c7c8b755f377a59ec62b94

Observation 767579a1-40fc-44cf-876e-98df49b56de9 · outbound

This paper cites TapNet: Neural network augmented with task-adaptive projection for few-shot learning.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation TapNet: Neural network augmented with task-adaptive projection for few-shot learning

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:48.420898Z

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=2026-08-07T14:51:45.842257Z digest=sha256:0980fa2a42beb296da25db99ca1a9b8830b19a58729ecaa8d17a66e419cf7660

Observation ccc2fc5c-222f-402b-ae76-6186e863148d · outbound

This paper cites AP-10K: A benchmark for animal pose es- timation in the wild.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation AP-10K: A benchmark for animal pose es- timation in the wild

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:48.270895Z

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=2026-08-07T14:51:45.971249Z digest=sha256:d973fdfb00195df543eec81a28c78b96d07fb99c3186b74b7d5fc0f203d7ef92

Observation db6fbcde-c4a1-400f-8eaf-5480dd64a741 · outbound

This paper cites Human– robot collaborative interaction with human perception and action recognition.Neurocomputing, 563:126827, 2024.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Human– robot collaborative interaction with human perception and action recognition.Neurocomputing, 563:126827, 2024

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:48.122804Z

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=2026-08-07T14:51:46.066972Z digest=sha256:f00124b71674a8273bbbafe055daf1c81eb1d55ba3a9da6b105d8487e8242e0f

Observation dc161f9e-4c1f-47f6-bdc5-a1342fe6c235 · outbound

This paper cites HRFormer: High- resolution transformer for dense prediction.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation HRFormer: High- resolution transformer for dense prediction

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:47.945036Z

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=2026-08-07T14:51:46.131219Z digest=sha256:6925eaeb218cc2387fc0c23282f035cb4e61ef043b8f9616e7f86c314acabd8b

Observation bafc9414-4001-47a1-beaa-840b6646a839 · outbound

This paper cites Prototype completion with primitive knowl- edge for few-shot learning.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Prototype completion with primitive knowl- edge for few-shot learning

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:47.805067Z

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=2026-08-07T14:51:46.199240Z digest=sha256:02e92b8cf054bdd4022d7212b94ceab07b2d300046bc2e332ca7f32db1510819

Observation e61bd124-0dff-4109-b7d0-27c2035ac4e3 · outbound

This paper cites Uni3D: A unified baseline for multi-dataset 3D object detection.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Uni3D: A unified baseline for multi-dataset 3D object detection

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:47.671478Z

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=2026-08-07T14:51:46.279883Z digest=sha256:a7ae0a09a417db04952c12e64dea87c199058d1014db219f2fb6598fff9162bd

Observation 7b2eef6c-46ff-414f-af8b-471772e9d066 · outbound

This paper cites Pose2Seg: Detection free human instance segmentation.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Pose2Seg: Detection free human instance segmentation

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:47.476269Z

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=2026-08-07T14:51:46.349200Z digest=sha256:c44168b0ddce081cebfc46cfa942332ea0158bbc3890ea84863f96a88acf13c5

Observation d5b07968-2b95-4003-a7f5-e4469f555c72 · outbound

This paper cites Object detec- tion with a unified label space from multiple datasets.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Object detec- tion with a unified label space from multiple datasets

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:47.143817Z

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=2026-08-07T14:51:46.417964Z digest=sha256:4daf54269f4ff6dd07dfd4c6d04f8081712ebb1f98d5a2ecf15e7be0e135b5d7

Observation 91338eb1-4737-4a6d-9ecf-9400f2e86213 · outbound

This paper cites Rethinking Semantic Segmentation: A Prototype View.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Rethinking Semantic Segmentation: A Prototype View

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:46.970605Z

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=2026-08-07T14:51:46.490587Z digest=sha256:253472a314410da12954003cbe804845fa32019d25a583b99a87e177010dd9e4

Observation 276478b7-d61a-4fb4-aac7-01eba36b475c · outbound

This paper cites Sim- ple multi-dataset detection.

PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation Sim- ple multi-dataset detection

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:51:46.802670Z

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=2026-08-07T14:51:46.600152Z digest=sha256:3998d841a13fb2f1acf5e78706707bc8c67522e4959818803080c381a23651d6

Pith citing papers

No inbound Pith citation observations are available.