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MoCRA: Mixture of Compositional Rank-1 Atoms for 4K All-in-One Video Restoration
Yongcong Wang, Pu Wang, Hingchin Chen +8
Real-world video arrives hazy, rainy, dark, or noisy, and a deployable restorer faces three demands at once: no degradation label, native 4K output, and stability in playback. Exis…
LiBrA-Net: Lie-Algebraic Bilateral Affine Fields for Real-Time 4K Video Dehazing
Yongcong Wang, Chengchao Shen, Guangwei Gao +5
Currently, there is a gap in the field of ultra-high-definition (UHD) video dehazing due to the lack of a benchmark for evaluation. Furthermore, existing video dehazing methods can…
Multiple Object Stitching for Unsupervised Representation Learning
Chengchao Shen, Dawei Liu, Jianxin Wang
Contrastive learning for single object centric images has achieved remarkable progress on unsupervised representation, but suffering inferior performance on the widespread images w…
Multi-Grained Contrast for Data-Efficient Unsupervised Representation Learning
Chengchao Shen, Jianzhong Chen, Jianxin Wang
The existing contrastive learning methods mainly focus on single-grained representation learning, e.g., part-level, object-level or scene-level ones, thus inevitably neglecting the…