38 citations · 55 across the 14 of their papers we have counts for
15 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.…
DF: World Modeling via Decoder-Free Feature Forecasting in Autonomous Navigation
Jiaming Chen, Guoan Xu, Aoshen Huang +3
Forecasting future states from video sequences is a critical challenge for autonomous robotic systems and a fundamental objective of world modeling. Prior generative methods operat…
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…
JointSplat: Probabilistic Joint Flow-Depth Optimization for Sparse-View Gaussian Splatting
Yang Xiao, Guoan Xu, Qiang Wu +1
Reconstructing 3D scenes from sparse viewpoints is a long-standing challenge with wide applications. Recent advances in feed-forward 3D Gaussian sparse-view reconstruction methods…
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…
MacFormer: Semantic Segmentation with Fine Object Boundaries
Guoan Xu, Wenfeng Huang, Tao Wu +5
Semantic segmentation involves assigning a specific category to each pixel in an image. While Vision Transformer-based models have made significant progress, current semantic segme…
HAFormer: Unleashing the Power of Hierarchy-Aware Features for Lightweight Semantic Segmentation
Guoan Xu, Wenjing Jia, Tao Wu +2
Both Convolutional Neural Networks (CNNs) and Transformers have shown great success in semantic segmentation tasks. Efforts have been made to integrate CNNs with Transformer models…
MFPNet: Multi-scale Feature Propagation Network For Lightweight Semantic Segmentation
Guoan Xu, Wenjing Jia, Tao Wu +1
In contrast to the abundant research focusing on large-scale models, the progress in lightweight semantic segmentation appears to be advancing at a comparatively slower pace. Howev…
Lightweight Real-time Semantic Segmentation Network with Efficient Transformer and CNN
Guoan Xu, Juncheng Li, Guangwei Gao +3
In the past decade, convolutional neural networks (CNNs) have shown prominence for semantic segmentation. Although CNN models have very impressive performance, the ability to captu…
FBSNet: A Fast Bilateral Symmetrical Network for Real-Time Semantic Segmentation
Guangwei Gao, Guoan Xu, Juncheng Li +3
Real-time semantic segmentation, which can be visually understood as the pixel-level classification task on the input image, currently has broad application prospects, especially i…
MSCFNet: A Lightweight Network With Multi-Scale Context Fusion for Real-Time Semantic Segmentation
Guangwei Gao, Guoan Xu, Yi Yu +3
In recent years, how to strike a good trade-off between accuracy and inference speed has become the core issue for real-time semantic segmentation applications, which plays a vital…