X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation | Paper Citation Record

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

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation 2d human pose estimation: New benchmark and state of the art analysis

Reference 1

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Observation d0c9799a-ef5a-4388-9fb7-e6343ae1cf57 · outbound

This paper cites Who left the dogs out?: 3D animal reconstruction with expectation maximization in the loop.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Who left the dogs out?: 3D animal reconstruction with expectation maximization in the loop

Reference 2

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Observation dadeb7d8-b4b6-41a5-8f9c-3a99664e5b74 · outbound

This paper cites Within the Dynamic Context: Inertia-aware 3D Human Modeling with Pose Sequence.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Within the Dynamic Context: Inertia-aware 3D Human Modeling with Pose Sequence

Reference 3

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This paper cites Expressive Whole-Body Control for Humanoid Robots.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Expressive Whole-Body Control for Humanoid Robots

Reference 4

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Observation 58a2de69-c687-43d3-92df-d6777cdc58cb · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Imagenet: A large-scale hierarchical image database

Reference 5

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This paper cites Unsupervised learning of disentangled representations from video.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Unsupervised learning of disentangled representations from video

Reference 6

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Observation 8fcffdf0-eeea-44cc-94a4-6da3c67248df · outbound

This paper cites 3d human reconstruction in the wild with synthetic data using generative models.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation 3d human reconstruction in the wild with synthetic data using generative models

Reference 7

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Observation a20524ca-1471-425d-9e50-a906c9fe41b7 · outbound

This paper cites Multiple choice learning: Learning to produce multiple structured outputs.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Multiple choice learning: Learning to produce multiple structured outputs

Reference 8

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Observation 808fcb13-0e6e-4e78-bb54-1b1c595e940f · outbound

This paper cites Inductive representation learning on large graphs.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Inductive representation learning on large graphs

Reference 9

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Observation 75283b92-461c-47bc-bb4c-cda3ed329425 · outbound

This paper cites Multiple view ge- ometry in computer vision.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Multiple view ge- ometry in computer vision

Reference 10

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Observation 2444cab9-ad25-4e6f-a94a-c4b7be7adc6c · outbound

This paper cites Deep residual learning for image recognition.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Deep residual learning for image recognition

Reference 11

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Observation 24f234fa-3483-4107-81fe-ade700bd5636 · outbound

This paper cites Autolink: Self-supervised learning of human skeletons and object out- lines by linking keypoints.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Autolink: Self-supervised learning of human skeletons and object out- lines by linking keypoints

Reference 12

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Observation ec06fb4f-9137-4ce8-beac-e745085b1c87 · outbound

This paper cites Unsupervised 3d keypoint es- timation with multi-view geometry.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Unsupervised 3d keypoint es- timation with multi-view geometry

Reference 13

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Observation 30e460b4-6a8b-4b02-98e1-98f03e93bc48 · outbound

This paper cites Temporal representation learning on monocular videos for 3d human pose estimation.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Temporal representation learning on monocular videos for 3d human pose estimation

Reference 14

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This paper cites an unresolved cited work.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Unresolved cited work

Reference 15

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Observation 9e130914-f2a8-4b32-b17d-9acb53b0d0ed · outbound

This paper cites Learning high fi- delity depths of dressed humans by watching social media dance videos.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Learning high fi- delity depths of dressed humans by watching social media dance videos

Reference 16

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Observation ff7f2e40-e4e0-483b-b968-9b3b4c98fcf3 · outbound

This paper cites Unsupervised learning of object landmarks through conditional image generation.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Unsupervised learning of object landmarks through conditional image generation

Reference 17

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Observation db5cda0b-969f-4036-89b8-4e2022bd1c74 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Adam: A Method for Stochastic Optimization

Reference 18

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Observation 8caf5813-60ca-47c1-924a-68367edffddf · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Semi-Supervised Classification with Graph Convolutional Networks

Reference 19

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Observation 173b0ec1-e0c8-4264-9653-63e3f9930f14 · outbound

This paper cites Self-supervised 3d human pose estimation via part guided novel image synthesis.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Self-supervised 3d human pose estimation via part guided novel image synthesis

Reference 20

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Observation 6c87904a-b96b-41de-84fa-9d0b6fac7515 · outbound

This paper cites Kinematic-structure-preserved representation for unsupervised 3d human pose estimation.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Kinematic-structure-preserved representation for unsupervised 3d human pose estimation

Reference 21

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Observation 329689f6-4d82-46a4-9d34-36402474604e · outbound

This paper cites Stochastic multiple choice learning for training diverse deep ensembles.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Stochastic multiple choice learning for training diverse deep ensembles

Reference 22

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Observation a72c38cd-299a-4054-a8b5-060858a58f01 · outbound

This paper cites Human pose regression with residual log-likelihood estimation.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Human pose regression with residual log-likelihood estimation

Reference 23

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Observation bc8baba1-f91f-40c5-8467-40eb9056e527 · outbound

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

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Mhformer: Multi-hypothesis transformer for 3d human pose estimation

Reference 24

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Observation edf63595-42fa-4bdd-8093-81f5186c4597 · outbound

This paper cites Smpl: A skinned multi- person linear model.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Smpl: A skinned multi- person linear model

Reference 25

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Observation 550af59a-83e1-431d-9eeb-6d79b51d6caf · outbound

This paper cites Perpetual humanoid control for real-time simulated avatars.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Perpetual humanoid control for real-time simulated avatars

Reference 26

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Observation 1b0eecfb-0218-4f35-9388-148f41beb45b · outbound

This paper cites Least squares genera- tive adversarial networks.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Least squares genera- tive adversarial networks

Reference 27

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Observation 2d907827-1bea-4ada-8f88-dc85d556fd2f · outbound

This paper cites Monocular 3d human pose estimation in the wild using improved cnn supervision.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Monocular 3d human pose estimation in the wild using improved cnn supervision

Reference 28

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This paper cites Agora: Avatars in geography optimized for regression analysis.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Agora: Avatars in geography optimized for regression analysis

Reference 29

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Observation 2ac7aa5b-933b-4c77-ae32-be1657b27595 · outbound

This paper cites Learning to estimate 3d human pose and shape from a single color image.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Learning to estimate 3d human pose and shape from a single color image

Reference 30

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Observation 1bb1f286-febc-4b67-bab5-a9ddc4174d64 · outbound

This paper cites Improving 2d human pose estimation in rare camera views with synthetic data.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Improving 2d human pose estimation in rare camera views with synthetic data

Reference 31

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This paper cites Neural scene decomposi- tion for multi-person motion capture.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Neural scene decomposi- tion for multi-person motion capture

Reference 32

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Observation abbec9a5-f981-48a1-af99-6512b93599da · outbound

This paper cites Barc: Learning to regress 3d dog shape from images by exploiting breed information.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Barc: Learning to regress 3d dog shape from images by exploiting breed information

Reference 33

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Observation a1a9ac40-d169-428f-968b-8d8b6b3b1498 · outbound

This paper cites Unsu- pervised human pose estimation through transforming shape templates.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Unsu- pervised human pose estimation through transforming shape templates

Reference 34

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Observation 3013a507-9d63-45a9-a3d5-a6ce2e3fb441 · outbound

This paper cites Syn- thetic training for accurate 3d human pose and shape esti- mation in the wild.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Syn- thetic training for accurate 3d human pose and shape esti- mation in the wild

Reference 35

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This paper cites Ntu rgb+ d: A large scale dataset for 3d human activity anal- ysis.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Ntu rgb+ d: A large scale dataset for 3d human activity anal- ysis

Reference 36

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Observation 514f3480-72ad-4adf-956c-2eb2f2ef6c0a · outbound

This paper cites Skeleton-based action recognition with directed graph neu- ral networks.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Skeleton-based action recognition with directed graph neu- ral networks

Reference 37

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This paper cites Two- stream adaptive graph convolutional networks for skeleton- based action recognition.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Two- stream adaptive graph convolutional networks for skeleton- based action recognition

Reference 38

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This paper cites Self-supervised 3d human pose estimation from a single image.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Self-supervised 3d human pose estimation from a single image

Reference 39

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Observation d374647f-aace-4329-b5ea-e3caf59b4cf2 · outbound

This paper cites Selfpose3d: Self-supervised multi-person multi-view 3d pose estimation.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Selfpose3d: Self-supervised multi-person multi-view 3d pose estimation

Reference 40

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This paper cites Bkind-3d: Self-supervised 3d keypoint discovery from multi-view videos.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Bkind-3d: Self-supervised 3d keypoint discovery from multi-view videos

Reference 41

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Observation def57bea-47d8-47ae-b86d-5a1169e2de34 · outbound

This paper cites Integral human pose regression.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Integral human pose regression

Reference 42

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Observation 89543014-e2c3-4a7d-bef5-088625c71475 · outbound

This paper cites Discovery of latent 3d key- points via end-to-end geometric reasoning.Advances in Neu- ral Information Processing Systems, 31, 2018.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Discovery of latent 3d key- points via end-to-end geometric reasoning.Advances in Neu- ral Information Processing Systems, 31, 2018

Reference 43

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This paper cites Visualizing data using t-sne.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Visualizing data using t-sne

Reference 44

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This paper cites Learning from synthetic humans.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Learning from synthetic humans

Reference 45

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Observation 89030cab-412f-41a4-af8e-f2a2c5e2a95f · outbound

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

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Recovering accurate 3d human pose in the wild using imus and a moving camera

Reference 46

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Observation 7b594fc8-b900-474d-810c-ee61ed35c235 · outbound

This paper cites Canonpose: Self-supervised monocu- lar 3d human pose estimation in the wild.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Canonpose: Self-supervised monocu- lar 3d human pose estimation in the wild

Reference 47

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Observation 830599c6-a8d4-4498-a096-86c76ffd2c64 · outbound

This paper cites Spatial tempo- ral graph convolutional networks for skeleton-based action recognition.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Spatial tempo- ral graph convolutional networks for skeleton-based action recognition

Reference 48

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This paper cites Mask as supervi- sion: Leveraging unified mask information for unsupervised 3d pose estimation.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Mask as supervi- sion: Leveraging unified mask information for unsupervised 3d pose estimation

Reference 49

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Observation c33cf3b9-4ba6-4107-8b78-d90be1562ddf · outbound

This paper cites Synbody: Synthetic dataset with layered human models for 3d human perception and modeling.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Synbody: Synthetic dataset with layered human models for 3d human perception and modeling

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:00:02.034666Z

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Observation 53a8dbf3-e428-4aa5-8174-d5f60e2458e9 · outbound

This paper cites Towards alleviating the mod- eling ambiguity of unsupervised monocular 3d human pose estimation.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Towards alleviating the mod- eling ambiguity of unsupervised monocular 3d human pose estimation

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:00:02.016747Z

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Observation dce61f32-588a-4a85-9217-0af2244802ff · outbound

This paper cites Unsupervised discovery of object land- marks as structural representations.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Unsupervised discovery of object land- marks as structural representations

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:00:01.998374Z

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Observation 293758f8-831c-4173-a459-41b391b33c00 · outbound

This paper cites an unresolved cited work.

X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-12T17:00:01.979023Z

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