Ligeng Chen
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View article: MacFormer: Semantic Segmentation with Fine Object Boundaries
MacFormer: Semantic Segmentation with Fine Object Boundaries Open
Semantic segmentation involves assigning a specific category to each pixel in an image. While Vision Transformer-based models have made significant progress, current semantic segmentation methods often struggle with precise predictions in …
View article: Image recoloring for color vision deficiency compensation using Swin transformer
Image recoloring for color vision deficiency compensation using Swin transformer Open
People with color vision deficiency (CVD) have difficulty in distinguishing differences between colors. To compensate for the loss of color contrast experienced by CVD individuals, a lot of image recoloring approaches have been proposed. H…
View article: HAFormer: Unleashing the Power of Hierarchy-Aware Features for Lightweight Semantic Segmentation
HAFormer: Unleashing the Power of Hierarchy-Aware Features for Lightweight Semantic Segmentation Open
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 to capture both local and global context interactions. How…
View article: MFPNet: Multi-scale Feature Propagation Network For Lightweight Semantic Segmentation
MFPNet: Multi-scale Feature Propagation Network For Lightweight Semantic Segmentation Open
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. However, existing compact methods often suffer from limited feat…
View article: Nimbus: Toward Speed Up Function Signature Recovery via Input Resizing and Multi-Task Learning
Nimbus: Toward Speed Up Function Signature Recovery via Input Resizing and Multi-Task Learning Open
Function signature recovery is important for many binary analysis tasks such as control-flow integrity enforcement, clone detection, and bug finding. Existing works try to substitute learning-based methods with rule-based methods to reduce…
View article: AVMiner: Expansible and Semantic-Preserving Anti-Virus Labels Mining Method
AVMiner: Expansible and Semantic-Preserving Anti-Virus Labels Mining Method Open
With the increase in the variety and quantity of malware, there is an urgent need to speed up the diagnosis and the analysis of malware. Extracting the malware family-related tokens from AV (Anti-Virus) labels, provided by online anti-viru…
View article: RoBin: Facilitating the Reproduction of Configuration-Related Vulnerability
RoBin: Facilitating the Reproduction of Configuration-Related Vulnerability Open
Vulnerability reproduction paves a way in debugging software failures, which need intensive manual efforts. However, some key factors (e.g., software configuration, trigger method) are often missing, so we can not directly reproduce the fa…