Chaozheng Wu — accepted AI-conference papers

2021

3D AffordanceNet: A Benchmark for Visual Object Affordance Understanding

Shengheng Deng, Xun Xu, Chaozheng Wu, Ke Chen, Kui Jia

CVPR 2021poster

The ability to understand the ways to interact with objects from visual cues, a.k.a. visual affordance, is essential to vision-guided robotic research. This involves categorizing, segmenting and reasoning of visual affordance. Relevant studies in 2D and 2.5D image domains have been made previously,…

Cited by 136 PDF ↗code ↗Scholar ↗

2020

Grasp Proposal Networks: An End-to-End Solution for Visual Learning of Robotic Grasps

Chaozheng Wu, Jian Chen, Qiaoyu Cao, Jianchi Zhang, Yunxin Tai, Lin Sun +1

NeurIPS 2020poster

Learning robotic grasps from visual observations is a promising yet challenging task. Recent research shows its great potential by preparing and learning from large-scale synthetic datasets. For the popular, 6 degree-of-freedom (6-DOF) grasp setting of parallel-jaw gripper, most of existing methods…

Cited by 63 Source ↗PDF ↗code ↗Scholar ↗