Cross-benchmarking between SOTA methods
for OSR and OOD detection.

Discover novel categories in a continuous stream of unlabeled data while mitigating the challenge of catastrophic forgetting.

A region-based image editing method
offers faster and more precise image editing.

Unsupervised problem of extracting multiple concepts
from a single image.

DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Models.

Visual AI Lab (VAIL) is a research group directed by Prof. Kai Han, working on computer vision, machine learning, and artificial intelligence, under the Division of Statistics and Actuarial Science, School of Computing and Data Science, The University of Hong Kong. The overarching goal of our research is to achieve principled and comprehensive visual understanding, close the intelligence gap between machines and humans, and build reliable AI systems for open-world use. Our current research focuses on open-world learning, 3D vision, generative AI, foundation models and their relevant fields.

🚩 Openings:
(1) PhD students: We are always looking for strong students to work on exciting research problems (☞ fellowships and scholarships).
(2) Postdocs: Positions in computer vision and deep learning are available.
Please drop Prof. Kai Han an email with your resume if you are interested in working with us.