I am currently a PhD Student at Computer Vision Lab, ETH Zürich, Switzerland. I am co-supervised by Prof. Luc Van Gool and Prof. Radu Timofte. I also work closely with Dr. Kai Zhang. I mainly focus on low-level vision research, especially on image and video restoration, such as super-resolution, deblurring and denoising.
An interpretable method based on alternating optimization. It takes low-framerate low-resolution blurry videos as inputs and can deal with video deblurring, frame interpolation and super-resolution problems in a joint way.
A reference-based image super-resolution Transformer with state-of-the-art performance. It consists of texture feature encoder module, reference-based deformable attention module and residual feature aggregation module.
A transformer-based model that jointly extracts, aligns, and fuses frame features at multiple scales; state-of-the-art performance in video SR/ deblurring/ denoising.
A transformer-based model that jointly extracts, aligns, and fuses frame features at multiple scales; state-of-the-art performance in video SR/ deblurring/ denoising/ frame interpolation/ space-time video SR.
A transformer-based image restoration that allows content-based interactions and long-range dependency modelling; state-of-the-art performance on image SR, denoising and JPEG compression artifact reduction.
It learns a bijective mapping between HR and LR image pairs by modelling low and high-frequency components; a unified framework for image SR and image rescaling.