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Found 5 papers, 1 papers with code
DiffPose: SpatioTemporal Diffusion Model for Video-Based Human Pose Estimation
However, extending such models to multi-frame human pose estimation is non-trivial due to the presence of the additional temporal dimension in videos.
Clothes Grasping and Unfolding Based on RGB-D Semantic Segmentation
These methods often utilize physics engines to synthesize depth images to reduce the cost of real labeled data collection.
Mutual Information-Based Temporal Difference Learning for Human Pose Estimation in Video
On the other hand, the temporal difference has the ability to encode representative motion information which can potentially be valuable for pose estimation but has not been fully exploited.
Learning the Network of Graphs for Graph Neural Networks
Our model solves the first issue by simultaneously learning multiple relation graphs of data samples as well as a relation network of graphs, and solves the second and the third issue by selecting important data features as well as important data sample relations.
Temporal Feature Alignment and Mutual Information Maximization for Video-Based Human Pose Estimation
State-of-the-art methods strive to incorporate additional visual evidences from neighboring frames (supporting frames) to facilitate the pose estimation of the current frame (key frame).
