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20202026
most citedAdversarial Semantic Data Augmentation for Human Pose Estimation

3 citations · 3 across the 3 of their papers we have counts for

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8 papers · 1 filter

cs.CV2026

Fusing Transferred Priors and Physics-based Decomposition for Underwater Image Enhancement

Haochen Hu, Yanrui Bin, Zhengyan Zhang +3

The underwater images are captured within diverse water-medium conditions, leading to complex degradation, including color bias, low contrast, and blur effect. Recently, learning-b…

cs.CV2026

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision

Haochen Hu, Yanrui Bin, Chih-yung Wen +1

Underwater Image Enhancement (UIE) is essential for mitigating degradations caused by water medium. Although learning-based methods have advanced significantly, most rely on paired…

cs.CV2025

NormalCrafter: Learning Temporally Consistent Normals from Video Diffusion Priors

Yanrui Bin, Wenbo Hu, Haoyuan Wang +2

Surface normal estimation serves as a cornerstone for a spectrum of computer vision applications. While numerous efforts have been devoted to static image scenarios, ensuring tempo…

cs.CV2024

Learning 3D-Aware GANs from Unposed Images with Template Feature Field

Xinya Chen, Hanlei Guo, Yanrui Bin +5

Collecting accurate camera poses of training images has been shown to well serve the learning of 3D-aware generative adversarial networks (GANs) yet can be quite expensive in pract…

cs.CV20231 cited

VeRi3D: Generative Vertex-based Radiance Fields for 3D Controllable Human Image Synthesis

Xinya Chen, Jiaxin Huang, Yanrui Bin +2

Unsupervised learning of 3D-aware generative adversarial networks has lately made much progress. Some recent work demonstrates promising results of learning human generative models…

cs.CV2020

Adversarial Refinement Network for Human Motion Prediction

Xianjin Chao, Yanrui Bin, Wenqing Chu +6

Human motion prediction aims to predict future 3D skeletal sequences by giving a limited human motion as inputs. Two popular methods, recurrent neural networks and feed-forward dee…