62 citations · 304 across the 51 of their papers we have counts for
6 papers · 1 filter
Criteria Comparative Learning for Real-scene Image Super-Resolution
Yukai Shi, Hao Li, Sen Zhang +2
Real-scene image super-resolution aims to restore real-world low-resolution images into their high-quality versions. A typical RealSR framework usually includes the optimization of…
DnSwin: Toward Real-World Denoising via Continuous Wavelet Sliding-Transformer
Hao Li, Zhijing Yang, Xiaobin Hong +4
Real-world image denoising is a practical image restoration problem that aims to obtain clean images from in-the-wild noisy inputs. Recently, the Vision Transformer (ViT) has exhib…
Real-World Image Super-Resolution by Exclusionary Dual-Learning
Hao Li, Jinghui Qin, Zhijing Yang +4
Real-world image super-resolution is a practical image restoration problem that aims to obtain high-quality images from in-the-wild input, has recently received considerable attent…
Dual-Perspective Semantic-Aware Representation Blending for Multi-Label Image Recognition with Partial Labels
Tao Pu, Tianshui Chen, Hefeng Wu +3
Despite achieving impressive progress, current multi-label image recognition (MLR) algorithms heavily depend on large-scale datasets with complete labels, making collecting large-s…
Heterogeneous Semantic Transfer for Multi-label Recognition with Partial Labels
Tianshui Chen, Tao Pu, Lingbo Liu +3
Multi-label image recognition with partial labels (MLR-PL), in which some labels are known while others are unknown for each image, may greatly reduce the cost of annotation and th…
Exploring Negatives in Contrastive Learning for Unpaired Image-to-Image Translation
Yupei Lin, Sen Zhang, Tianshui Chen +3
Unpaired image-to-image translation aims to find a mapping between the source domain and the target domain. To alleviate the problem of the lack of supervised labels for the source…