19 citations · 55 across the 9 of their papers we have counts for
9 papers
Five A Network: You Only Need 9K Parameters for Underwater Image Enhancement
Jingxia Jiang, Tian Ye, Jinbin Bai +5
A lightweight underwater image enhancement network is of great significance for resource-constrained platforms, but balancing model size, computational efficiency, and enhancement…
NightHazeFormer: Single Nighttime Haze Removal Using Prior Query Transformer
Yun Liu, Zhongsheng Yan, Sixiang Chen +3
Nighttime image dehazing is a challenging task due to the presence of multiple types of adverse degrading effects including glow, haze, blurry, noise, color distortion, and so on.…
DEHRFormer: Real-time Transformer for Depth Estimation and Haze Removal from Varicolored Haze Scenes
Sixiang Chen, Tian Ye, Jun Shi +4
Varicolored haze caused by chromatic casts poses haze removal and depth estimation challenges. Recent learning-based depth estimation methods are mainly targeted at dehazing first…
RSFDM-Net: Real-time Spatial and Frequency Domains Modulation Network for Underwater Image Enhancement
Jingxia Jiang, Jinbin Bai, Yun Liu +4
Underwater images typically experience mixed degradations of brightness and structure caused by the absorption and scattering of light by suspended particles. To address this issue…
Dual-former: Hybrid Self-attention Transformer for Efficient Image Restoration
Sixiang Chen, Tian Ye, Yun Liu +1
Recently, image restoration transformers have achieved comparable performance with previous state-of-the-art CNNs. However, how to efficiently leverage such architectures remains a…
SnowFormer: Context Interaction Transformer with Scale-awareness for Single Image Desnowing
Sixiang Chen, Tian Ye, Yun Liu +1
Due to various and complicated snow degradations, single image desnowing is a challenging image restoration task. As prior arts can not handle it ideally, we propose a novel transf…
Towards Real-time High-Definition Image Snow Removal: Efficient Pyramid Network with Asymmetrical Encoder-decoder Architecture
Tian Ye, Sixiang Chen, Yun Liu +2
In winter scenes, the degradation of images taken under snow can be pretty complex, where the spatial distribution of snowy degradation is varied from image to image. Recent method…
MSP-Former: Multi-Scale Projection Transformer for Single Image Desnowing
Sixiang Chen, Tian Ye, Yun Liu +4
Snow removal causes challenges due to its characteristic of complex degradations. To this end, targeted treatment of multi-scale snow degradations is critical for the network to le…
Towards Efficient Single Image Dehazing and Desnowing
Tian Ye, Sixiang Chen, Yun Liu +2
Removing adverse weather conditions like rain, fog, and snow from images is a challenging problem. Although the current recovery algorithms targeting a specific condition have made…