Generalized Category Discovery:
A new and realistic open-world problem.

JIFF reconstructs the 3D human model from a single image with detailed face geometry.

Open-Set Recognition: a Good Closed-set Classifier is All You Need?

Visual Artificial Intelligence Lab (VAiL) is a research group working on computer vision, deep learning, and machine learning, under Department of Statistics and Actuarial Science, The University of Hong Kong, directed by Dr. Kai Han. Our goal is to achieve principled and comprehensive visual understanding for real applications of artificial intelligent systems. Our recent research focuses on open-world learning, general representation learning, 3D vision and their relevant fileds, spanning topics like generalized/novel category discovery, open-set recognition, out-of-distribution detection, multimodal learning, foundation models, vision-language models, learning from limited data, semi-supervised learning, long-tailed learning, visual correspondence, 3D reconstruction (object/human/scene), image matting, photometric stereo, etc.

🚩Openings:
(1) We are always looking for strong PhD students to work on exciting computer vision research problems (☞ fellowships and scholarships) -- 2023 intake applications on-going.
(2) Postdoc positions in computer vision and deep learning are available, with a competitive salary.
(3) Summer Research Programme 2023 is now open for application (deadline: Jan 27, 2023 ☞ more more details), with the possiblity of conditional PhD offer of 2024 intake with HKU-PS scholarship.
Please drop Dr. Kai Han an email with your resume if you are interested in working with us.