Yiye Chen
I am a Georgia Tech ECE Ph.D student
under the supervision of the Prof. Patricio Vela.
I am a member of the Vision-based Manipulation group (VisMan)
in the IVALab.
Prior to that, I obtained my B.Eng from the Image Processing Center, Beihang University (BUAA).
I did my undergrad thesis under the supervision of
Prof. Xiangzhi Bai
and Prof. Bindang Xue.
My research interest covers computer vision, machine learning,
and their applications in the robotic manipulation.
Email  / 
Google Scholar  / 
LinkedIn  / 
Github
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Research (* means equal contribution)
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WDiscOOD: Out-of-Distribution Detection via Whitened Linear Discriminative Analysis
Yiye Chen,
Yunzhi Lin,
Ruinian Xu,
Patricio A. Vela
In submission, 2023
paper
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KGNv2: Separating Scale and Pose Prediction for Keypoint-based 6-DoF Grasp Synthesis on RGB-D input
Yiye Chen,
Ruinian Xu,
Yunzhi Lin,
Hongyi Chen*,
Patricio A. Vela
Submitted to International Conference on Intelligent Robots and Systems (IROS), 2023
paper /
video /
code
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Planning with Language Models through Iterative Energy Minimization
Hongyi Chen*,
Yilun Du*,
Yiye Chen*,
Patricio A. Vela
Joshua B. Tenenbaum
International Conference on Learning Representations (ICLR), 2023
paper /
project /
code
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Keypoint-GraspNet: Keypoint-based 6-DoF Grasp Generation from the Monocular RGB-D input
Yiye Chen,
Yunzhi Lin,
Ruinian Xu,
Patricio A. Vela
IEEE International Conference on Robotics and Automation (ICRA), 2023
paper /
video /
code
A 6-DoF grasp deteciton approach based on RGB-D input.
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A Joint Network for Grasp Detection Conditioned on Natural Language
Commands
Yiye Chen,
Ruinian Xu,
Yunzhi Lin,
Patricio A. Vela
IEEE International Conference on Robotics and Automation (ICRA), 2021
paper /
video
An end-to-end network that detects grasps affilicated to the target required by a natural language command.
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Simultaneous Multi-Level Descriptor Learning and Semantic
Segmentation for Domain-Specific Relocalization
Xiaolong Wu*,
Yiye Chen*,
Cédric Pradalier,
Patricio A. Vela
IEEE International Conference on Robotics and Automation (ICRA), 2021
paper
A dense multi-level descriptor learning framework for cross-season localization.
We designed a descriptor segmentation module to inject high-level information into the descriptor space from the guidance of semantic labels
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- Conference Reviewer: IROS2023
- Journal/Letter Reviewer: RA-L
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