31 citations · 89 across the 11 of their papers we have counts for
19 papers
Self-Supervised Intensity-Event Stereo Matching
Jinjin Gu, Jinan Zhou, Ringo Sai Wo Chu +5
Event cameras are novel bio-inspired vision sensors that output pixel-level intensity changes in microsecond accuracy with a high dynamic range and low power consumption. Despite t…
Efficient Image Super-Resolution using Vast-Receptive-Field Attention
Lin Zhou, Haoming Cai, Jinjin Gu +5
The attention mechanism plays a pivotal role in designing advanced super-resolution (SR) networks. In this work, we design an efficient SR network by improving the attention mechan…
Super-Resolution by Predicting Offsets: An Ultra-Efficient Super-Resolution Network for Rasterized Images
Jinjin Gu, Haoming Cai, Chenyu Dong +4
Rendering high-resolution (HR) graphics brings substantial computational costs. Efficient graphics super-resolution (SR) methods may achieve HR rendering with small computing resou…
Blueprint Separable Residual Network for Efficient Image Super-Resolution
Zheyuan Li, Yingqi Liu, Xiangyu Chen +4
Recent advances in single image super-resolution (SISR) have achieved extraordinary performance, but the computational cost is too heavy to apply in edge devices. To alleviate this…
NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results
Ren Yang, Radu Timofte, Meisong Zheng +75
This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…
Blind Image Super-Resolution: A Survey and Beyond
Anran Liu, Yihao Liu, Jinjin Gu +2
Blind image super-resolution (SR), aiming to super-resolve low-resolution images with unknown degradation, has attracted increasing attention due to its significance in promoting r…