70 citations · 194 across the 14 of their papers we have counts for
4 papers · 1 filter
Learning from History: Task-agnostic Model Contrastive Learning for Image Restoration
Gang Wu, Junjun Jiang, Kui Jiang +1
Contrastive learning has emerged as a prevailing paradigm for high-level vision tasks, which, by introducing properly negative samples, has also been exploited for low-level vision…
Fully Convolutional Network for Lightweight Image Super-Resolution
Gang Wu, Junjun Jiang, Kui Jiang +1
Deep models have achieved significant process on single image super-resolution (SISR) tasks, in particular large models with large kernel ( or more). However, the heavy c…
The RoboDepth Challenge: Methods and Advancements Towards Robust Depth Estimation
Lingdong Kong, Yaru Niu, Shaoyuan Xie +39
Accurate depth estimation under out-of-distribution (OoD) scenarios, such as adverse weather conditions, sensor failure, and noise contamination, is desirable for safety-critical a…
Incorporating Transformer Designs into Convolutions for Lightweight Image Super-Resolution
Gang Wu, Junjun Jiang, Yuanchao Bai +1
In recent years, the use of large convolutional kernels has become popular in designing convolutional neural networks due to their ability to capture long-range dependencies and pr…