no code implementations • 23 Feb 2024 • Zekang Yang, Wang Zeng, Sheng Jin, Chen Qian, Ping Luo, Wentao Liu
Automated machine learning (AutoML) is a collection of techniques designed to automate the machine learning development process.
no code implementations • 28 Aug 2023 • Ruijie Yao, Sheng Jin, Lumin Xu, Wang Zeng, Wentao Liu, Chen Qian, Ping Luo, Ji Wu
Multi-Label Image Recognition (MLIR) is a challenging task that aims to predict multiple object labels in a single image while modeling the complex relationships between labels and image regions.
1 code implementation • 21 Jul 2022 • Lumin Xu, Sheng Jin, Wang Zeng, Wentao Liu, Chen Qian, Wanli Ouyang, Ping Luo, Xiaogang Wang
In this paper, we introduce the task of Category-Agnostic Pose Estimation (CAPE), which aims to create a pose estimation model capable of detecting the pose of any class of object given only a few samples with keypoint definition.
Ranked #4 on 2D Pose Estimation on MP-100
1 code implementation • CVPR 2022 • Wang Zeng, Sheng Jin, Wentao Liu, Chen Qian, Ping Luo, Wanli Ouyang, Xiaogang Wang
Vision transformers have achieved great successes in many computer vision tasks.
Ranked #4 on 2D Human Pose Estimation on COCO-WholeBody
3 code implementations • CVPR 2020 • Wang Zeng, Wanli Ouyang, Ping Luo, Wentao Liu, Xiaogang Wang
This paper proposes a model-free 3D human mesh estimation framework, named DecoMR, which explicitly establishes the dense correspondence between the mesh and the local image features in the UV space (i. e. a 2D space used for texture mapping of 3D mesh).
Ranked #1 on 3D Human Reconstruction on Surreal