Research Interest - Computer Vision and Deep Learning
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Image/video/3D point cloud understanding, segmentation, and detection
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Image editing and enhancement, e.g., image restoration, low-light enhancement, deblur and super-resolution
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Image/video/3D object/ 3D scene generation and reconstruction
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Multi-modal AI
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Other cutting-edge research in deep learning, e.g., semi- and self-supervised learning, knowledge distillation, few-shot learning, NAS, and AutoML
Open-source codebase
https://github.com/dvlab-research
Challenges
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No. 1 of MEDIA AI Alibaba Challenge in Video Human Segmentation track 2020
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No. 1 of Apollo 3D Object Detection Challenge 2019
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No. 1 of Instance Segmentation Track in Scene Understanding Challenge for Autonomous Navigation in Unstructured Environments 2018 (PANet)
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No. 1 of WAD Drivable Area Segmentation Challenge 2018 (PSANet)
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No. 1 of LSUN Semantic Segmentation Challenge 2017 (PSPNet)
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No. 1 of COCO Detection Challenge in Instance Segmentation track 2017 (PANet)
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No. 2 of COCO Detection Challenge in Object Detection track 2017 (PANet)
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No. 1 of LSUN Instance Segmentation Challenge 2017 (PANet)
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No. 1 of ImageNet Scene Parsing Challenge 2016 (PSPNet)
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No. 3 of COCO Detection Challenge in Instance Segmentation track 2015
Deep Vision Lab
A top-tier research institute on computer vision and machine learning