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20212026
most citedSingle Underwater Image Enhancement Using an Analysis-Synthesis Network

9 citations · 11 across the 6 of their papers we have counts for

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cs.CV2026

The Fourth Challenge on Image Super-Resolution (4) at NTIRE 2026: Benchmark Results and Method Overview

Zheng Chen, Kai Liu, Jingkai Wang +150

This paper presents the NTIRE 2026 image super-resolution (4) challenge, one of the associated competitions of the NTIRE 2026 Workshop at CVPR 2026. The challenge aims to r…

cs.CV2025

GAME: Learning Multimodal Interactions via Graph Structures for Personality Trait Estimation

Kangsheng Wang, Yuhang Li, Chengwei Ye +5

Apparent personality analysis from short videos poses significant chal-lenges due to the complex interplay of visual, auditory, and textual cues. In this paper, we propose GAME, a…

cs.CV2025

GaMNet: A Hybrid Network with Gabor Fusion and NMamba for Efficient 3D Glioma Segmentation

Chengwei Ye, Huanzhen Zhang, Yufei Lin +3

Gliomas are aggressive brain tumors that pose serious health risks. Deep learning aids in lesion segmentation, but CNN and Transformer-based models often lack context modeling or d…

cs.CV20212 cited

Domain Adaptation for Underwater Image Enhancement

Zhengyong Wang, Liquan Shen, Mei Yu +3

Recently, learning-based algorithms have shown impressive performance in underwater image enhancement. Most of them resort to training on synthetic data and achieve outstanding per…

cs.CV20219 cited

Single Underwater Image Enhancement Using an Analysis-Synthesis Network

Zhengyong Wang, Liquan Shen, Mei Yu +2

Most deep models for underwater image enhancement resort to training on synthetic datasets based on underwater image formation models. Although promising performances have been ach…