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20242026
most citedFrequency-aware Feature Fusion for Dense Image Prediction

3 citations · 7 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Fourier Angle Alignment for Oriented Object Detection in Remote Sensing

Changyu Gu, Linwei Chen, Lin Gu +1

In remote sensing rotated object detection, mainstream methods suffer from two bottlenecks, directional incoherence at detector neck and task conflict at detecting head. Ulitising…

cs.CV2025

Spatial Frequency Modulation for Semantic Segmentation

Linwei Chen, Ying Fu, Lin Gu +2

High spatial frequency information, including fine details like textures, significantly contributes to the accuracy of semantic segmentation. However, according to the Nyquist-Shan…

cs.CV2025

Frequency-Dynamic Attention Modulation for Dense Prediction

Linwei Chen, Lin Gu, Ying Fu

Vision Transformers (ViTs) have significantly advanced computer vision, demonstrating strong performance across various tasks. However, the attention mechanism in ViTs makes each l…

cs.CV2025★ 2 cited

Frequency Dynamic Convolution for Dense Image Prediction

Linwei Chen, Lin Gu, Liang Li +2

While Dynamic Convolution (DY-Conv) has shown promising performance by enabling adaptive weight selection through multiple parallel weights combined with an attention mechanism, th…

cs.CV2024★ 3 cited

Frequency-aware Feature Fusion for Dense Image Prediction

Linwei Chen, Ying Fu, Lin Gu +3

Dense image prediction tasks demand features with strong category information and precise spatial boundary details at high resolution. To achieve this, modern hierarchical models o…

cs.CV2024

When Semantic Segmentation Meets Frequency Aliasing

Linwei Chen, Lin Gu, Ying Fu

Despite recent advancements in semantic segmentation, where and what pixels are hard to segment remains largely unexplored. Existing research only separates an image into easy and…

cs.CV2024★ 2 cited

Frequency-Adaptive Dilated Convolution for Semantic Segmentation

Linwei Chen, Lin Gu, Ying Fu

Dilated convolution, which expands the receptive field by inserting gaps between its consecutive elements, is widely employed in computer vision. In this study, we propose three st…