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cs.CV2026
Causal Disentanglement-Inspired Degradation Representation Learning for Full-Reference Image Quality Assessment
Zhen Zhang, Jielei Chu, Tian Zhang +5
Existing deep network-based full-reference image quality assessment (FR-IQA) models typically work by performing pairwise comparisons of deep features from the reference and distor…
cs.CV2026
Degradation-Aware Adaptive Context Gating for Unified Image Restoration
Lei He, Jielei Chu, Fengmao Lv +4
Unified image restoration using a single model often faces task interference due to diverse degradations. To address this, we propose DACG-IR (Degradation-Aware Adaptive Context Ga…
cs.CV2024
Dataset Awareness is not Enough: Implementing Sample-level Tail Encouragement in Long-tailed Self-supervised Learning
Haowen Xiao, Guanghui Liu, Xinyi Gao +3
Self-supervised learning (SSL) has shown remarkable data representation capabilities across a wide range of datasets. However, when applied to real-world datasets with long-tailed…