56 citations · 401 across the 55 of their papers we have counts for
88 papers
Learning Single Image Defocus Deblurring with Misaligned Training Pairs
Yu Li, Dongwei Ren, Xinya Shu +1
By adopting popular pixel-wise loss, existing methods for defocus deblurring heavily rely on well aligned training image pairs. Although training pairs of ground-truth and blurry i…
Self-Supervised Image Restoration with Blurry and Noisy Pairs
Zhilu Zhang, Rongjian Xu, Ming Liu +2
When taking photos under an environment with insufficient light, the exposure time and the sensor gain usually require to be carefully chosen to obtain images with satisfying visua…
Reversed Image Signal Processing and RAW Reconstruction. AIM 2022 Challenge Report
Marcos V. Conde, Radu Timofte, Yibin Huang +40
Cameras capture sensor RAW images and transform them into pleasant RGB images, suitable for the human eyes, using their integrated Image Signal Processor (ISP). Numerous low-level…
Learning Dual Memory Dictionaries for Blind Face Restoration
Xiaoming Li, Shiguang Zhang, Shangchen Zhou +2
To improve the performance of blind face restoration, recent works mainly treat the two aspects, i.e., generic and specific restoration, separately. In particular, generic restorat…
From Face to Natural Image: Learning Real Degradation for Blind Image Super-Resolution
Xiaoming Li, Chaofeng Chen, Xianhui Lin +2
How to design proper training pairs is critical for super-resolving real-world low-quality (LQ) images, which suffers from the difficulties in either acquiring paired ground-truth…
ImaginaryNet: Learning Object Detectors without Real Images and Annotations
Minheng Ni, Zitong Huang, Kailai Feng +1
Without the demand of training in reality, humans can easily detect a known concept simply based on its language description. Empowering deep learning with this ability undoubtedly…