most citedTCPFormer: Learning Temporal Correlation with Implicit Pose Proxy for 3D Human Pose Estimation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2025

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…

cs.CL2025

Refine Medical Diagnosis Using Generation Augmented Retrieval and Clinical Practice Guidelines

Wenhao Li, Hongkuan Zhang, Hongwei Zhang +5

Current medical language models, adapted from large language models (LLMs), typically predict ICD code-based diagnosis from electronic health records (EHRs) because these labels ar…

cs.CV20251 cited

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…

cs.CV2025

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…

cs.CV2024

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…

cs.CV2024

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…