Search Results for author: Qian Bao

Found 9 papers, 4 papers with code

TRACE: 5D Temporal Regression of Avatars with Dynamic Cameras in 3D Environments

3 code implementations CVPR 2023 Yu Sun, Qian Bao, Wu Liu, Tao Mei, Michael J. Black

Although the estimation of 3D human pose and shape (HPS) is rapidly progressing, current methods still cannot reliably estimate moving humans in global coordinates, which is critical for many applications.

3D Human Pose Estimation regression

WOC: A Handy Webcam-based 3D Online Chatroom

no code implementations2 Sep 2022 Chuanhang Yan, Yu Sun, Qian Bao, Jinhui Pang, Wu Liu, Tao Mei

We develop WOC, a webcam-based 3D virtual online chatroom for multi-person interaction, which captures the 3D motion of users and drives their individual 3D virtual avatars in real-time.

Smart Director: An Event-Driven Directing System for Live Broadcasting

no code implementations11 Jan 2022 Yingwei Pan, Yue Chen, Qian Bao, Ning Zhang, Ting Yao, Jingen Liu, Tao Mei

To our best knowledge, our system is the first end-to-end automated directing system for multi-camera sports broadcasting, completely driven by the semantic understanding of sports events.

Event Detection Highlight Detection

Recent Advances in Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective

no code implementations23 Apr 2021 Wu Liu, Qian Bao, Yu Sun, Tao Mei

We believe this survey will provide the readers with a deep and insightful understanding of monocular human pose estimation.

3D Human Pose Estimation

Neural Architecture Search for Joint Human Parsing and Pose Estimation

1 code implementation ICCV 2021 Dan Zeng, Yuhang Huang, Qian Bao, Junjie Zhang, Chi Su, Wu Liu

With the spirit of NAS, we propose to search for an efficient network architecture (NPPNet) to tackle two tasks at the same time.

Human Parsing Neural Architecture Search +1

Synthetic Training for Monocular Human Mesh Recovery

no code implementations27 Oct 2020 Yu Sun, Qian Bao, Wu Liu, Wenpeng Gao, Yili Fu, Chuang Gan, Tao Mei

To solve this problem, we design a multi-branch framework to disentangle the regression of different body properties, enabling us to separate each component's training in a synthetic training manner using unpaired data available.

Computational Efficiency Human Mesh Recovery

Monocular, One-stage, Regression of Multiple 3D People

2 code implementations ICCV 2021 Yu Sun, Qian Bao, Wu Liu, Yili Fu, Michael J. Black, Tao Mei

Through a body-center-guided sampling process, the body mesh parameters of all people in the image are easily extracted from the Mesh Parameter map.

 Ranked #1 on 3D Multi-Person Mesh Recovery on Relative Human (using extra training data)

3D Depth Estimation 3D Multi-Person Mesh Recovery +2

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