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Found 2 papers, 0 papers with code
Two-Stage Co-Segmentation Network Based on Discriminative Representation for Recovering Human Mesh From Videos
However, most of the existing methods focus on the temporal consistency of videos, while ignoring the spatial representation in complex scenes, thus failing to recover a reasonable and smooth human mesh sequence under extreme illumination and chaotic backgrounds. To alleviate this problem, we propose a two-stage co-segmentation network based on discriminative representation for recovering human body meshes from videos.
Spatio-temporal Tendency Reasoning for Human Body Pose and Shape Estimation from Videos
Different from them, our STR aims to learn accurate and natural motion sequences in an unconstrained environment through temporal and spatial tendency and to fully excavate the spatio-temporal features of existing video data.
Ranked #55 on
3D Human Pose Estimation
on MPI-INF-3DHP
