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20242026
most citedGMapLatent: Geometric Mapping in Latent Space

1 citations · 1 across the 8 of their papers we have counts for

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cs.CV2026

Coupled Optimal Transport with Landmark Constraints

Xiang Gu, Jian Sun, Zongben Xu

Existing optimal transport (OT) models primarily seek an OT map or plan between distributions by minimizing a prescribed transport cost or distortion. However, minimizing transport…

cs.CV2025

BaryIR: Learning Multi-Source Unified Representation in Continuous Barycenter Space for Generalizable All-in-One Image Restoration

Xiaole Tang, Xiaoyi He, Xiang Gu +1

Despite remarkable advances made in all-in-one image restoration (AIR) for handling different types of degradations simultaneously, existing methods remain vulnerable to out-of-dis…

cs.CV20251 cited

GMapLatent: Geometric Mapping in Latent Space

Wei Zeng, Xuebin Chang, Jianghao Su +3

Cross-domain generative models based on encoder-decoder AI architectures have attracted much attention in generating realistic images, where domain alignment is crucial for generat…

cs.CV2024

Degradation-Aware Residual-Conditioned Optimal Transport for Unified Image Restoration

Xiaole Tang, Xiang Gu, Xiaoyi He +2

All-in-one image restoration has emerged as a practical and promising low-level vision task for real-world applications. In this context, the key issue lies in how to deal with dif…

cs.CV2024

Residual-Conditioned Optimal Transport: Towards Structure-Preserving Unpaired and Paired Image Restoration

Xiaole Tang, Xin Hu, Xiang Gu +1

Deep learning-based image restoration methods generally struggle with faithfully preserving the structures of the original image. In this work, we propose a novel Residual-Conditio…