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SOTA
弱监督三维人体姿态估计
Weakly Supervised 3D Human Pose Estimation On
Weakly Supervised 3D Human Pose Estimation On
评估指标
Average MPJPE (mm)
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Average MPJPE (mm)
Paper Title
Repository
Rhodin et al.
131.7
Unsupervised Geometry-Aware Representation for 3D Human Pose Estimation
Pavlakos et al.
118.4
Harvesting Multiple Views for Marker-less 3D Human Pose Annotations
-
Pavlakos et al.
110.7
TexturePose: Supervising Human Mesh Estimation with Texture Consistency
HW-HuP
104.1
Heuristic Weakly Supervised 3D Human Pose Estimation
self-supervised mocap
98.4
Self-supervised Learning of Motion Capture
RepNet
89.9
RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation
Li et al.
88.8
On Boosting Single-Frame 3D Human Pose Estimation via Monocular Videos
-
Tome et al.
88.4
Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image
Wang et al.
83.0
Distill Knowledge from NRSfM for Weakly Supervised 3D Pose Learning
-
EpipolarPose (self-supervised)
76.6
Self-Supervised Learning of 3D Human Pose using Multi-view Geometry
CanonPose
74.3
CanonPose: Self-Supervised Monocular 3D Human Pose Estimation in the Wild
GeoRep
67.4
Weakly-Supervised 3D Human Pose Learning via Multi-view Images in the Wild
-
EpipolarPose (S1)
65.35
Self-Supervised Learning of 3D Human Pose using Multi-view Geometry
Triangulation
64.7
On Triangulation as a Form of Self-Supervision for 3D Human Pose Estimation
-
Pavllo et al.
64.7
3D human pose estimation in video with temporal convolutions and semi-supervised training
TriPose
62.9
TriPose: A Weakly-Supervised 3D Human Pose Estimation via Triangulation from Video
-
Li et al.
62.9
Cascaded deep monocular 3D human pose estimation with evolutionary training data
2D-3D Lifting self-supervised
62.0
Self-Supervised 3D Human Pose Estimation with Multiple-View Geometry
EpipolarPose (SS + RU)
60.56
Self-Supervised Learning of 3D Human Pose using Multi-view Geometry
GeoRep (semi-supervised)
59.7
Weakly-Supervised 3D Human Pose Learning via Multi-view Images in the Wild
-
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