Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning | Paper Citation Record

Observation f2234ee6-dafd-46fd-a37c-0f5db742eae6 · outbound

This paper cites Enhanced skeleton visualization for view invariant human action recognition,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Enhanced skeleton visualization for view invariant human action recognition,

Reference 1

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Observation 4b9c7f81-fa6e-4925-8463-87c633696868 · outbound

This paper cites 3d human pose estimation= 2d pose estimation+ matching,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning 3d human pose estimation= 2d pose estimation+ matching,

Reference 2

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Observation da2ee21b-0fca-4357-9078-a540e263bbe5 · outbound

This paper cites Pose2mesh: graph convolutional network for 3d human pose and mesh recovery from a 2d human pose,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Pose2mesh: graph convolutional network for 3d human pose and mesh recovery from a 2d human pose,

Reference 3

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Observation fbbc0f2c-2d8d-428f-9b62-f7907d84ba26 · outbound

This paper cites Recognizing human actions as the evolution of pose estimation maps,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Recognizing human actions as the evolution of pose estimation maps,

Reference 4

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Observation 2a50ac69-9789-421b-898a-1d123724ba1a · outbound

This paper cites Milnet: multiplex interactive learning network for rgb-t semantic segmentation,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Milnet: multiplex interactive learning network for rgb-t semantic segmentation,

Reference 5

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Observation a7002d79-835b-482f-a795-2ecf15cbadd8 · outbound

This paper cites Dynamic dense graph convolutional network for skeleton-based human motion prediction,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Dynamic dense graph convolutional network for skeleton-based human motion prediction,

Reference 6

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Observation d121e9e2-1ac7-40c8-838c-a59427f1e9ea · outbound

This paper cites Symbiotic graph neural networks for 3d skeleton-based human action recognition and motion prediction,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Symbiotic graph neural networks for 3d skeleton-based human action recognition and motion prediction,

Reference 7

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Observation c48b03aa-99e4-4a32-a1e1-378264fb9858 · outbound

This paper cites Tcpformer: learning temporal correlation with implicit pose proxy for 3d human pose estimation,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Tcpformer: learning temporal correlation with implicit pose proxy for 3d human pose estimation,

Reference 8

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Observation efdc6811-d3ed-4ba1-b849-729e945a7d1f · outbound

This paper cites Hourglass tokenizer for efficient transformer-based 3d human pose estimation,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Hourglass tokenizer for efficient transformer-based 3d human pose estimation,

Reference 9

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Observation abec7183-60f0-440c-ab27-850da2a3e975 · outbound

This paper cites Feature boosting network for 3d pose estimation,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Feature boosting network for 3d pose estimation,

Reference 10

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Observation 4d1848ec-188a-459f-a387-49acf865db0d · outbound

This paper cites Arts: semi-analytical regressor using disentangled skeletal representations for human mesh recovery from videos,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Arts: semi-analytical regressor using disentangled skeletal representations for human mesh recovery from videos,

Reference 11

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Observation 3c6b6d50-15af-491c-97cf-0dcf85c8723c · outbound

This paper cites Attention is all you need,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Attention is all you need,

Reference 12

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Observation 96b0b821-a7a6-4557-9c9f-cb8a1a45c071 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 13

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Observation bf386c47-8156-41a1-84c9-f3bfd4949508 · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 14

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Observation ec706d76-1894-4980-ab49-df3a1b7c972c · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 15

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Observation 6d637a48-858f-44a3-9f84-2c5d03e130f3 · outbound

This paper cites Language models are few-shot learners,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Language models are few-shot learners,

Reference 16

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Observation b03bc53c-ada6-4357-b3d5-dc9575a25b2b · outbound

This paper cites Spatial temporal graph convolutional networks for skeleton-based action recognition,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Spatial temporal graph convolutional networks for skeleton-based action recognition,

Reference 17

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Observation 51ca7f08-3935-4ab6-8f16-8d7775c4f218 · outbound

This paper cites Motionbert: a unified perspective on learning human motion representations,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Motionbert: a unified perspective on learning human motion representations,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.672321Z

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Observation b29937ce-19d0-4e8e-8231-a961e47014e6 · outbound

This paper cites Unified pose sequence modeling,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Unified pose sequence modeling,

Reference 19

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Observation b321b7c5-5832-4523-b7e3-3a055c08baab · outbound

This paper cites Large motion model for unified multi-modal motion generation,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Large motion model for unified multi-modal motion generation,

Reference 20

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Observation 34ae6273-930f-4ebb-a379-c00bff8496ed · outbound

This paper cites Unihcp: a unified model for human-centric perceptions,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Unihcp: a unified model for human-centric perceptions,

Reference 21

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Observation d7e9cc2c-0402-44d0-9737-088958a68ce8 · outbound

This paper cites Macdiff: unified skeleton modeling with masked conditional diffusion,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Macdiff: unified skeleton modeling with masked conditional diffusion,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.600362Z

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Observation 37d9d7df-fe86-42bd-acb6-c0928d4953b3 · outbound

This paper cites History repeats itself: Human motion prediction via motion attention,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning History repeats itself: Human motion prediction via motion attention,

Reference 23

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Observation e813fba3-e40e-4ab0-ba66-c251a5b89e42 · outbound

This paper cites Gcnext: towards the unity of graph convolutions for human motion prediction,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Gcnext: towards the unity of graph convolutions for human motion prediction,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.572534Z

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Observation 09c5bfd1-d94c-49e4-abe1-da24b53d089f · outbound

This paper cites Towards accurate 3d human motion prediction from incomplete observations,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Towards accurate 3d human motion prediction from incomplete observations,

Reference 25

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Observation c001674a-5665-4228-8f4c-64229b7284c6 · outbound

This paper cites What Makes Good In-Context Examples for GPT-$3$?.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning What Makes Good In-Context Examples for GPT-$3$?

Reference 26

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Observation 5c9d2085-66ca-4888-b396-55d16a93f082 · outbound

This paper cites What makes good examples for visual in-context learning?.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning What makes good examples for visual in-context learning?

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.542677Z

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Observation 941d44bc-0ce0-4e77-a9c6-d25309e9d4fd · outbound

This paper cites Images speak in images: a generalist painter for in-context visual learning,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Images speak in images: a generalist painter for in-context visual learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.528380Z

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Observation 21ba3675-5d85-489c-9ee8-568ec4c39c57 · outbound

This paper cites Explore in-context learning for 3d point cloud understanding,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Explore in-context learning for 3d point cloud understanding,

Reference 29

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Observation 958268ff-8ca2-4a8a-b5b6-bac1d3d6c128 · outbound

This paper cites Skeleton-in-context: unified skeleton sequence modeling with in-context learning,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Skeleton-in-context: unified skeleton sequence modeling with in-context learning,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.498802Z

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Observation ccdd0062-2e61-4492-934a-e44244a24b2b · outbound

This paper cites On human motion prediction using recurrent neural networks,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning On human motion prediction using recurrent neural networks,

Reference 31

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Observation 69598f5b-f8a0-43c2-b644-522e264599f9 · outbound

This paper cites Convolutional sequence to sequence model for human dynamics,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Convolutional sequence to sequence model for human dynamics,

Reference 32

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Observation cc315047-919b-42a5-a863-6ea349f95b1c · outbound

This paper cites Multiscale spatio-temporal graph neural networks for 3d skeleton-based motion prediction,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Multiscale spatio-temporal graph neural networks for 3d skeleton-based motion prediction,

Reference 33

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Observation cef44e3c-d47d-47f9-a6fb-f7a26e77d735 · outbound

This paper cites Learning trajectory dependen- cies for human motion prediction,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Learning trajectory dependen- cies for human motion prediction,

Reference 34

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Observation 5ad5db41-1888-4b45-8a92-3ea482347748 · outbound

This paper cites Spatiotemporal co- attention recurrent neural networks for human-skeleton motion prediction,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Spatiotemporal co- attention recurrent neural networks for human-skeleton motion prediction,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.423180Z

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Observation 1352af83-154a-4e51-a6f9-1ea3a36fe958 · outbound

This paper cites A simple yet effective baseline for 3d human pose estimation,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning A simple yet effective baseline for 3d human pose estimation,

Reference 36

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Observation fc8c304f-c0a5-4bb6-ad88-e831860551b2 · outbound

This paper cites Mixste: seq2seq mixed spatio-temporal encoder for 3d human pose estimation in video,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Mixste: seq2seq mixed spatio-temporal encoder for 3d human pose estimation in video,

Reference 37

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Observation 6c8c58c0-afbe-4de4-ba7d-9c1cb4577015 · outbound

This paper cites Mhformer: multi- hypothesis transformer for 3d human pose estimation,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Mhformer: multi- hypothesis transformer for 3d human pose estimation,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.380010Z

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Observation 34dc57c4-79d5-4e09-a425-2860570be418 · outbound

This paper cites Diffpose: toward more reliable 3d pose estimation,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Diffpose: toward more reliable 3d pose estimation,

Reference 39

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Observation b4dabecc-d2b9-48c1-b6e5-08e3915daf91 · outbound

This paper cites App: adaptive pose pooling for 3d human pose estimation from videos,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning App: adaptive pose pooling for 3d human pose estimation from videos,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.350790Z

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Observation 4bec8d95-9931-4f9b-a7b3-a05cdf7eb5cb · outbound

This paper cites Finepose: fine-grained prompt-driven 3d human pose estimation via diffusion models,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Finepose: fine-grained prompt-driven 3d human pose estimation via diffusion models,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.336239Z

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Observation 465b2311-dac8-43c6-a95c-b21f44e9ce93 · outbound

This paper cites Hybrik: a hybrid analytical-neural inverse kinematics solution for 3d human pose and shape estimation,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Hybrik: a hybrid analytical-neural inverse kinematics solution for 3d human pose and shape estimation,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.321187Z

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Observation 229aad97-cb21-482f-be89-27e4c0ce0049 · outbound

This paper cites Skeleton2mesh: kinematics prior injected unsupervised human mesh recovery,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Skeleton2mesh: kinematics prior injected unsupervised human mesh recovery,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.305175Z

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Observation fe4b286f-76d0-476a-8924-01c6ed1db2f8 · outbound

This paper cites Convolutional sequence generation for skeleton-based action synthesis,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Convolutional sequence generation for skeleton-based action synthesis,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.290924Z

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Observation d15e8113-9986-41e5-88df-78712f1e606f · outbound

This paper cites Generative Tweening: Long-term Inbetweening of 3D Human Motions.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Generative Tweening: Long-term Inbetweening of 3D Human Motions

Reference 45

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Observation 698a9f31-d72c-49ab-b83e-d04ee89e3d54 · outbound

This paper cites Convolutional autoencoders for human motion infilling,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Convolutional autoencoders for human motion infilling,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.275710Z

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Observation 75bc0eb0-0881-40f4-9e11-fd6092ee5f96 · outbound

This paper cites Human motion prediction via spatio-temporal inpainting,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Human motion prediction via spatio-temporal inpainting,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.260643Z

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Observation 8d12a375-b6ef-4d92-85b2-cb4031f204dc · outbound

This paper cites Coupled action recognition and pose estimation from multiple views,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Coupled action recognition and pose estimation from multiple views,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.244679Z

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Observation 0fa20059-9aa4-4be8-a84b-e69000053c79 · outbound

This paper cites SMPL: a skinned multi-person linear model,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning SMPL: a skinned multi-person linear model,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.229367Z

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Observation 9c0acd44-8cee-4334-8bed-2328e4032352 · outbound

This paper cites Keep it smpl: automatic estimation of 3d human pose and shape from a single image,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Keep it smpl: automatic estimation of 3d human pose and shape from a single image,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.214218Z

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Observation 5ee82fdd-8b67-44cc-9f26-f2f34be607a2 · outbound

This paper cites Unsupervised learning of view-invariant action representations,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Unsupervised learning of view-invariant action representations,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.197664Z

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Observation 1673257c-c979-451c-8156-38ee36121916 · outbound

This paper cites Motion guided 3d pose estimation from videos,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Motion guided 3d pose estimation from videos,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.181970Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 09c253df-4757-4e23-890b-69039fd05a9b · outbound

This paper cites Human3. 6m: large scale datasets and predictive methods for 3d human sensing in natural environments,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Human3. 6m: large scale datasets and predictive methods for 3d human sensing in natural environments,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.167412Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 79d580d8-3bab-4f80-94eb-fa0e9e93dabb · outbound

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

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Recovering accurate 3d human pose in the wild using imus and a moving camera,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.151861Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4b284715-f235-4aad-9cb9-9822e7e6eaf9 · outbound

This paper cites Amass: archive of motion capture as surface shapes,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Amass: archive of motion capture as surface shapes,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.137159Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 76e1f000-4b66-4096-8043-73f1126f787f · outbound

This paper cites Freeman: towards benchmarking 3d human pose estimation under real-world conditions,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Freeman: towards benchmarking 3d human pose estimation under real-world conditions,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.122712Z

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Observation 5926cb96-246c-446e-adde-60b35539f9b0 · outbound

This paper cites Ntu rgb+ d: a large scale dataset for 3d human activity analysis,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Ntu rgb+ d: a large scale dataset for 3d human activity analysis,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.107823Z

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Observation 4a071d6d-5357-4651-89ec-d43fd002eb15 · outbound

This paper cites Ntu rgb+ d 120: a large-scale benchmark for 3d human activity understanding,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Ntu rgb+ d 120: a large-scale benchmark for 3d human activity understanding,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.092245Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c9339566-c42f-4990-a0a9-40f6e13705b9 · outbound

This paper cites Disentangling and unifying graph convolutions for skeleton-based action recognition,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Disentangling and unifying graph convolutions for skeleton-based action recognition,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.076844Z

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Observation 8902fd96-a278-4cc9-96b7-3d4bac2f63c5 · outbound

This paper cites Vg4d: vision- language model goes 4d video recognition,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Vg4d: vision- language model goes 4d video recognition,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.061638Z

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Observation f55d2071-0ffb-4ee4-9114-443819550db7 · outbound

This paper cites A comprehensive study of weight sharing in graph networks for 3d human pose estimation,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning A comprehensive study of weight sharing in graph networks for 3d human pose estimation,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.046662Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9ae664b1-a258-4ab3-9ab4-8a5f5c6d3076 · outbound

This paper cites Progressively generating better initial guesses towards next stages for high-quality human motion prediction,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Progressively generating better initial guesses towards next stages for high-quality human motion prediction,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.031940Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2dcf241b-0530-4d07-8c28-84146619e7db · outbound

This paper cites Graph stacked hourglass networks for 3d human pose estimation,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Graph stacked hourglass networks for 3d human pose estimation,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.017162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1123d608-5cb4-47f8-b850-8c8934311254 · outbound

This paper cites Back to mlp: a simple baseline for human motion prediction,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Back to mlp: a simple baseline for human motion prediction,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:34.001620Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 93cf7b89-bcb8-4c72-bc13-3c23f4c01524 · outbound

This paper cites 3d human pose estimation in video with temporal convolutions and semi-supervised training,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning 3d human pose estimation in video with temporal convolutions and semi-supervised training,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.986124Z

Source-reported events for the cited work

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Observation d812e2ca-d1f5-4dcf-b722-5adcc1f98092 · outbound

This paper cites Co- occurrence feature learning for skeleton based action recognition using regularized deep lstm networks,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Co- occurrence feature learning for skeleton based action recognition using regularized deep lstm networks,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.971243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3a179ec5-2435-4001-a86a-b1d76cb588be · outbound

This paper cites Spatio-temporal lstm with trust gates for 3d human action recognition,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Spatio-temporal lstm with trust gates for 3d human action recognition,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.956141Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e6ce61b4-7998-4d85-99e1-6cc3ab76b2b1 · outbound

This paper cites Exploiting spatial-temporal relationships for 3d pose estimation via graph convolutional networks,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Exploiting spatial-temporal relationships for 3d pose estimation via graph convolutional networks,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.942375Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f66cf77c-7716-4be0-8b5b-28e4b9649e8e · outbound

This paper cites Learning dynamic relationships for 3d human motion prediction,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Learning dynamic relationships for 3d human motion prediction,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.928248Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 617b3566-bdf9-4e40-941e-0f853ef2a8d4 · outbound

This paper cites 3d human pose estimation with spatial and temporal transformers,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning 3d human pose estimation with spatial and temporal transformers,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.914303Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 17c609b1-5e7f-4f4f-ad14-0324f8b184c9 · outbound

This paper cites Graformer: graph-oriented transformer for 3d pose estimation,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Graformer: graph-oriented transformer for 3d pose estimation,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.900458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 73f99403-e17c-46c4-9837-1b25946377ef · outbound

This paper cites Motionagformer: enhancing 3d human pose estimation with a transformer-gcnformer network,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Motionagformer: enhancing 3d human pose estimation with a transformer-gcnformer network,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.886426Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 64a660f3-39d9-40f3-9bf8-478469c56129 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-15T17:36:33.126609Z

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Observation a976ad5a-181f-4238-ae9a-9b398d03db53 · outbound

This paper cites Pose Magic: Efficient and Temporally Consistent Human Pose Estimation with a Hybrid Mamba-GCN Network.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Pose Magic: Efficient and Temporally Consistent Human Pose Estimation with a Hybrid Mamba-GCN Network

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-15T17:36:33.131548Z

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Observation 5cd1ee38-c0fd-4a69-a0e7-b74ceb9a8fa5 · outbound

This paper cites Simba: Mamba augmented U-ShiftGCN for Skeletal Action Recognition in Videos.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Simba: Mamba augmented U-ShiftGCN for Skeletal Action Recognition in Videos

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-15T17:36:33.137387Z

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Observation beb3cd44-ab18-493d-a34b-d2c53bf2b91d · outbound

This paper cites Omg-seg: is one model good enough for all segmentation?.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Omg-seg: is one model good enough for all segmentation?

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.872885Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d26f3f1f-f117-45b5-8aec-1af7ce36af71 · outbound

This paper cites Seggpt: towards segmenting everything in context,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Seggpt: towards segmenting everything in context,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.859384Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3ad8f957-958a-40a7-8dad-15f7c65d3ce2 · outbound

This paper cites Learning to reconstruct 3d human pose and shape via model-fitting in the loop,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Learning to reconstruct 3d human pose and shape via model-fitting in the loop,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.845145Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 43d5e94f-bd20-4b01-97bd-d34d1d9c32e4 · outbound

This paper cites 2d/3d pose estimation and action recognition using multitask deep learning,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning 2d/3d pose estimation and action recognition using multitask deep learning,

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.830670Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c32b1851-7cee-4741-aec2-103370443433 · outbound

This paper cites A unified 3d human motion synthesis model via conditional variational auto-encoder,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning A unified 3d human motion synthesis model via conditional variational auto-encoder,

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.815717Z

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Observation 050e2942-5ebe-43e6-8be5-c6b8d60d8e73 · outbound

This paper cites Learning To Retrieve Prompts for In-Context Learning.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Learning To Retrieve Prompts for In-Context Learning

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-15T17:36:33.167288Z

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Observation 3ddf966e-6d26-4663-84fc-07562f836212 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Learning transferable visual models from natural language supervision,

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.801631Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation af196910-2a15-4e4d-96ac-42bc8d1ae89a · outbound

This paper cites In-Context Learning Unlocked for Diffusion Models.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning In-Context Learning Unlocked for Diffusion Models

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-15T17:36:33.176358Z

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Observation 36a8222a-7f05-4915-aad5-f97852e8da3c · outbound

This paper cites Visual prompting via image inpainting,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Visual prompting via image inpainting,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.787305Z

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Observation 96b51abc-e8dc-4d0e-828f-5c50e44cfc2a · outbound

This paper cites Explore in-context segmentation via latent diffusion models,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Explore in-context segmentation via latent diffusion models,

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.771610Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5bd2917e-76fa-4a3c-b4f7-a75115614151 · outbound

This paper cites Towards large-scale 3d representation learning with multi-dataset point prompt training,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Towards large-scale 3d representation learning with multi-dataset point prompt training,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.755852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 07377822-500e-4326-91ba-ecdc7e7e790c · outbound

This paper cites Exploring effec- tive factors for improving visual in-context learning,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Exploring effec- tive factors for improving visual in-context learning,

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-15T17:36:33.196620Z

Source-reported events for the cited work

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Observation af5435d5-86cc-4e28-a71f-dab41346e8d9 · outbound

This paper cites Mosh: motion and shape capture from sparse markers.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Mosh: motion and shape capture from sparse markers

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.741525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1c86798c-4f2e-45ae-bf97-7867659da004 · outbound

This paper cites End-to-end recovery of human shape and pose,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning End-to-end recovery of human shape and pose,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.726808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f2c0bbc6-8a48-4050-849a-726bf76f6de1 · outbound

This paper cites Pymaf: 3d human pose and shape regression with pyramidal mesh alignment feedback loop,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Pymaf: 3d human pose and shape regression with pyramidal mesh alignment feedback loop,

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.712347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 23310898-392b-403d-94f4-2845505148d9 · outbound

This paper cites 3d human pose estimation via non-causal retentive networks,.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning 3d human pose estimation via non-causal retentive networks,

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:36:33.584061Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2f53832f-e6b1-4184-8dea-fa1621a6ba88 · outbound

This paper cites an unresolved cited work.

Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning Unresolved cited work

Reference 2023

Resolution: parse uncertain; raw_fallback, observed 2026-08-15T17:36:34.658235Z

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