neuralchen Goto Github PK

followers: 152.0 following: 46.0 repos: 49.0 gists: 0.0

Name: Xuanhong Chen

Type: User

Company: Shanghai Jiao Tong University

Bio: Assistant professor at ICCI of Shanghai Jiao Tong University

Location: Shanghai,China

Xuanhong Chen

Email / Homepage / Google Scholar / Github

I'm an Assistant Professor at ICCI Shanghai Jiao Tong University, Shanghai, China. I mainly focus on image/video synthesis/editing and low-level vision research, especially on face attributes editing, such as:

Video Face Editing
Video Synthesis/Editing
MetaHuman
Image/Super Resolution
...

🚀 News

2023-12-12: Two papers are accepted by AAAI2024!
2023-07-14: One paper is accepted by ICCV2023!
2023-04-19: The code of OmniSR [Paper] (CVPR2023) is avaliable!
2023-03-24: The code of EQSR [Paper] (CVPR2023) is avaliable!
2023-03-22: The code of 3DQD [Paper] (CVPR2023) is avaliable!
2023-02-28: Three papers are accepted by CVPR 2023, codes will be avaliable ASAP. 😍
2022-11-20: One paper (GeoDSR) accepted by AAAI 2023.
2022-11-17: Im2Oil won the Top Paper Award (Best Paper Nomination) in ACM MM 2022. 😍
2022-09-15: One paper (RainNet) accepted by NeurIPS 2022.
2022-06-29: One paper (Im2Oil)) accepted by ACM MM 2022 (Top Paper Award 0.5%).
2021-12-10: One paper (Bivolution) accepted by AAAI2022.

🌱 Repositories

Topic	Title	Badge
Face Attributes Editing	SimSwap: An Efficient Framework For High Fidelity Face Swapping
Face Attributes Editing	SimSwap++: Towards Faster and High-Quality Identity Swapping
Face Attributes Editing	CooGAN: A Memory-Efficient Framework for High-Resolution Facial Attribute Editing
Stroke Based Rendering	Sketch Generation with Drawing Process Guided by Vector Flow and Grayscale
Style Transfer	Anisotropic Stroke Control for Multiple Artists Style Transfer
High Resolution Face Dataset	VGGFace2-HQ
Efficient Basic Operator	Bi-volution: A Static and Dynamic Coupled Filter
AI for Science	RainNet: A Large-Scale Imagery Dataset and Benchmark for Spatial Precipitation Downscaling
Low-level CV	Learning Continuous Depth Representation via Geometric Spatial Aggregator
Low-level CV	Deep Arbitrary-Scale Image Super-Resolution via Scale-Equivariance Pursuit
Low-level CV	Omni Aggregation Networks for Lightweight Image Super-Resolution