3 papers
cs.CV2026
Rethinking Efficient Crack Segmentation with Task-Aligned Structural-Directional Modeling
Shipeng Liu, Liang Zhao, Dengfeng Chen +1
Recent crack segmentation methods often follow generic semantic segmentation designs, using stronger backbones, hybrid CNN-Transformer-Mamba encoders, and auxiliary enhancement bra…
cs.CV2025
CLIC: Contrastive Learning Framework for Unsupervised Image Complexity Representation
Shipeng Liu, Liang Zhao, Dengfeng Chen
As a fundamental visual attribute, image complexity significantly influences both human perception and the performance of computer vision models. However, accurately assessing and…
cs.CV2025
CLICv2: Image Complexity Representation via Content Invariance Contrastive Learning
Shipeng Liu, Liang Zhao, Dengfeng Chen
Unsupervised image complexity representation often suffers from bias in positive sample selection and sensitivity to image content. We propose CLICv2, a contrastive learning framew…