I am a Lecturer (Assistant Professor)
affiliated with the Vision, Learning, and Control (VLC)
group in the School of Electronics and Computer Science (ECS)
at the University of Southampton
. My primary research is dedicated to advancing generative computer vision and continual machine learning within the context of artificial general intelligence. The overarching goal is to equip machines with a wide range of digital intelligences, encompassing rational, emotional, and imaginal aspects, in order to amplify and enhance biological intelligences. At present, I am particularly interested in exploring machine learning methodologies, including generative modeling, continual learning, and affective computing, to drive forward these research objectives.
I am looking for motivated and talented researchers/students to join our research group. Please have a look at the Openings and reach me if you are interested.
10/2023, We have openings for two more PhD positions: 'Generative Modeling in Computer Vision' and 'Deepfake Detection with Continual Learning'. Check out our published adverts (advert 1 and advert 2) or visit here for pre-application details!
02/2023, We are opening some positions for talents who are keen to publish papers, open source code, and make an impact.
02/2023, One interesting paper "Freestyle Layout-to-Image Synthesis" is accepted as a highlight (10% of accepted papers, 2.5% of submissions) to CVPR 2023. This paper introduces freestyle layout-to-image synthesis with diffusion generative network (FreestyleNet). The proposed FreestyleNet produces realistic-looking and creative images like ‘a warehouse running on a railroad’ and 'a hornless unicorn sitting on a bench'. Thanks all the reviewers for valuable comments and constructive suggestions!
01/2023, I join University of Southampton as a Lecturer (Assistant Professor) in Computer Science.
11/2022, One paper "An Efficient Recurrent Adversarial Framework for Unsupervised Real-Time Video Enhancement" gets accepted to IJCV.
11/2022, Two papers "Isolation and Impartial Aggregation: A Paradigm of Incremental Learning without Interference" and "Riemannian Local Mechanism for SPD Neural Networks" are accepted at AAAI 2023.
10/2022, One paper "Multi-agent Actor-Critic with Time Dynamical Opponent Model" gets accepted to Neurocomputing.
09/2022, One inspiring paper "S-Prompts Learning with Pre-trained Transformers: An Occam's Razor for Domain Incremental Learning" gets accepted to NeurIPS 2022. This paper proposes a rule-breaking continual learning paradigm (S-Prompts). It does not require the accumulation of the knowledge from previously learned domains. Instead, it merely learns the knowledge independently domain by domain, through simply prompting the state-of-the-art transformers.
08/2022, One paper "A Continual Deepfake Detection Benchmark: Dataset, Methods, and Essentials" gets accepted to WACV 2023.
06/2022, One paper "Trilevel Neural Architecture Search for Efficient Single Image Super-Resolution" is accepted by the CVPR-2022 NAS workshop.
03/2022, One paper "Generative Flows with Invertible Attentions" is accepted by CVPR 2022, with surprisingly increased final review scores (2 strong accepts and 2 borderline accepts). Thanks all the reviewers for the valuable comments and suggestions! This paper introduces an interesting idea of Invertible Transformer-based Attentions to Generative Normalizing Flows.
10/2021, One paper "Neural Architecture Search for Efficient Uncalibrated Deep Photometric Stereo" is accepted by WACV 2022.
09/2021, I join SMU Singapore as a tenure-track Assistant Professor in Computer Science.