5 papers
Next-Scale Prediction: A Self-Supervised Approach for Real-World Image Denoising
Yiwen Shan, Haiyu Zhao, Peng Hu +2
Self-supervised real-world image denoising remains a fundamental challenge, arising from the antagonistic trade-off between decorrelating spatially structured noise and preserving…
Learning with Dual-level Noisy Correspondence for Multi-modal Entity Alignment
Haobin Li, Yijie Lin, Peng Hu +2
Multi-modal entity alignment (MMEA) aims to identify equivalent entities across heterogeneous multi-modal knowledge graphs (MMKGs), where each entity is described by attributes fro…
DUDE: Diffusion-Based Unsupervised Cross-Domain Image Retrieval
Ruohong Yang, Peng Hu, Yunfan Li +1
Unsupervised cross-domain image retrieval (UCIR) aims to retrieve images of the same category across diverse domains without relying on annotations. Existing UCIR methods, which al…
MaIR: A Locality- and Continuity-Preserving Mamba for Image Restoration
Boyun Li, Haiyu Zhao, Wenxin Wang +3
Recent advancements in Mamba have shown promising results in image restoration. These methods typically flatten 2D images into multiple distinct 1D sequences along rows and columns…
DiFiC: Your Diffusion Model Holds the Secret to Fine-Grained Clustering
Ruohong Yang, Peng Hu, Xi Peng +2
Fine-grained clustering is a practical yet challenging task, whose essence lies in capturing the subtle differences between instances of different classes. Such subtle differences…