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 language prompting, 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.
News
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.
more news...
07/2021, One paper "Direct Differentiable Augmentation Search" is accepted by ICCV 2021.
04/2021, One paper "Neural Architecture Search of SPD Manifold Networks" is accepted by IJCAI 2021.
03/2021, Two papers "Efficient Conditional GAN Transfer with Knowledge Propagation across Classes" and "GANmut: Learning Interpretable Conditional Space for Gamut of Emotions" are accepted by CVPR 2021.
01/2021, One paper "Spectral Tensor Train Parameterization of Deep Learning Layers" is accepted by AISTATS 2021.
12/2020, One paper "Neural Architecture Search as Sparse Supernet" is accepted by AAAI 2021.
11/2020, One paper "Facial Emotion Recognition with Noisy Multi-task Annotations" is accepted by WACV 2021.
08/2020, One paper "AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results" will appear at the workshop AIM in conjunction with ECCV 2020.
07/2020, One paper "Weakly Paired Multi-Domain Image Translation" is accepted by BMVC 2020 as an oral.
07/2020, One paper "Off-Policy Reinforcement Learning for Efficient and Effective GAN Architecture Search" is accepted by ECCV 2020.
05/2020, We are organizing AIM Video Super-Resolution Challenge @ECCV 2020.
05/2020, One paper "NTIRE 2020 Challenge on Video Quality Mapping: Methods and Results" will appear at the workshop NTIRE in conjunction with CVPR 2020.
12/2019, We are organizing NTIRE Video Quality Mapping Challenge @CVPR 2020.
10/2019, One dataset paper "The Vid3oC and IntVID Datasets for Video Super Resolution and Quality Mapping" will appear at the workshop AIM in ICCV 2019.
10/2019, We are organizing a workshop "AIM: Advances in Image Manipulation Workshop and Challenges on Image and Video Manipulation"
and a tutorial "FIRE: From Image Restoration to Enhancement and Beyond" at ICCV, Oct. 27, 2019.
02/2019, One paper "Sliced Wasserstein Generative Models" is accepted by CVPR 2019. This paper was selected as one of the best publications of the week (20.04.2019), by DeepAI. Link to DeepAI Website
11/2018, One paper "Manifold-valued Image Generation with Wasserstein Generative Adversarial Nets" is accepted by AAAI 2019. This paper applies the theory of optimal transport on non-compact manifolds from Alessio Figalli (2018 Fields Medal winner) to generative modeling, which is able to generate photo-realistic biological samples.
07/2018, One paper "Wasserstein Divergence for GANs" is accepted by ECCV 2018.
04/2018, One paper "Covariance Pooling for Facial Expression Recognition" is accepted by the workshop DiffCVML in CVPR 2018.
11/2017, One paper "Cross Euclidean-to-Riemannian Metric Learning with Application to Face Recognition from Video" is accepted as a Regular Paper in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
11/2017, One paper "Building Deep Networks on Grassmann Manifolds" (GrNet) is accepted by AAAI 2018.
08/2017, One paper "Discriminant Analysis on Riemannian Manifold of Gaussian Distributions for Face Recognition with Image Sets" is accepted by IEEE Transactions on Image Processing (TIP).
07/2017, One paper "Geometry-aware Similarity Learning on SPD Manifolds for Visual Recognition" is accepted by IEEE Transactions on Circuits and Systems for Video Technology (TCSVT).
02/2017, One paper "Deep Learning on Lie Groups for Skeleton-based Action Recognition" (LieNet) is accepted as a spotlight by CVPR 2017. This paper proposes deep networks of Lie Groups for skeleton-based action recognition.
11/2016, One paper "A Riemannian Network for SPD Matrix Learning" (SPDNet) is accepted by AAAI 2017. This paper opens a new direction of deep manifold networks.
09/2015, I join ETH Zurich as a Postdoc Researcher in Computer Vision Lab.
|