1 citations · 2 across the 7 of their papers we have counts for
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HOT: Hierarchical Hourglass Tokenizer for Efficient Video Pose Transformers
Wenhao Li, Mengyuan Liu, Hong Liu +3
Transformers have been successfully applied in the field of video-based 3D human pose estimation. However, the high computational costs of these video pose transformers (VPTs) make…
TCPFormer: Learning Temporal Correlation with Implicit Pose Proxy for 3D Human Pose Estimation
Jiajie Liu, Mengyuan Liu, Hong Liu +1
Recent multi-frame lifting methods have dominated the 3D human pose estimation. However, previous methods ignore the intricate dependence within the 2D pose sequence and learn sing…
NanoHTNet: Nano Human Topology Network for Efficient 3D Human Pose Estimation
Jialun Cai, Mengyuan Liu, Hong Liu +2
The widespread application of 3D human pose estimation (HPE) is limited by resource-constrained edge devices, requiring more efficient models. A key approach to enhancing efficienc…
Dual-Branch Graph Transformer Network for 3D Human Mesh Reconstruction from Video
Tao Tang, Hong Liu, Yingxuan You +2
Human Mesh Reconstruction (HMR) from monocular video plays an important role in human-robot interaction and collaboration. However, existing video-based human mesh reconstruction m…
Depth: Self-Supervised Depth Estimation with Dynamic Mask in Dynamic Scenes
Siyu Chen, Hong Liu, Wenhao Li +3
Depth estimation is a crucial technology in robotics. Recently, self-supervised depth estimation methods have demonstrated great potential as they can efficiently leverage large am…
ARTS: Semi-Analytical Regressor using Disentangled Skeletal Representations for Human Mesh Recovery from Videos
Tao Tang, Hong Liu, Yingxuan You +2
Although existing video-based 3D human mesh recovery methods have made significant progress, simultaneously estimating human pose and shape from low-resolution image features limit…