1 citations · 1 across the 6 of their papers we have counts for
7 papers
URNet: A Unified Reparameterized Network for Efficient RGB-D Semantic Segmentation
Guoan Xu, Zhengxue Wang, Yang Xiao +3
Previous RGB-D semantic segmentation methods commonly employ dual encoders to separately process RGB and depth inputs, followed by dedicated modules for cross-modal feature fusion.…
RSGMamba: Reliability-Aware Self-Gated State Space Model for Multimodal Semantic Segmentation
Guoan Xu, Yang Xiao, Guangwei Gao +3
Multimodal semantic segmentation has emerged as a powerful paradigm for enhancing scene understanding by leveraging complementary information from multiple sensing modalities (e.g.…
WaveSeg: Enhancing Segmentation Precision via High-Frequency Prior and Mamba-Driven Spectrum Decomposition
Guoan Xu, Yang Xiao, Wenjing Jia +3
While recent semantic segmentation networks heavily rely on powerful pretrained encoders, most employ simplistic decoders, leading to suboptimal trade-offs between semantic context…
S2AFormer: Strip Self-Attention for Efficient Vision Transformer
Guoan Xu, Wenfeng Huang, Wenjing Jia +3
Vision Transformer (ViT) has made significant advancements in computer vision, thanks to its token mixer's sophisticated ability to capture global dependencies between all tokens.…
SCASeg: Strip Cross-Attention for Efficient Semantic Segmentation
Guoan Xu, Jiaming Chen, Wenfeng Huang +3
The Vision Transformer (ViT) has achieved notable success in computer vision, with its variants widely validated across various downstream tasks, including semantic segmentation. H…
Efficient Semantic Segmentation via Lightweight Multiple-Information Interaction Network
Yangyang Qiu, Guoan Xu, Guangwei Gao +3
Recently, integrating the local modeling capabilities of Convolutional Neural Networks (CNNs) with the global dependency strengths of Transformers has created a sensation in the se…
ReviveDiff: A Universal Diffusion Model for Restoring Images in Adverse Weather Conditions
Wenfeng Huang, Guoan Xu, Wenjing Jia +2
Images captured in challenging environments--such as nighttime, smoke, rainy weather, and underwater--often suffer from significant degradation, resulting in a substantial loss of…