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20212025
most citedLearning to Adapt to Light

64 citations · 103 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.CV2025

A biological vision inspired framework for machine perception of abutting grating illusory contours

Xiao Zhang, Kai-Fu Yang, Xian-Shi Zhang +3

Higher levels of machine intelligence demand alignment with human perception and cognition. Deep neural networks (DNN) dominated machine intelligence have demonstrated exceptional…

cs.CV2024★ 1 cited

Weak Supervision with Arbitrary Single Frame for Micro- and Macro-expression Spotting

Wang-Wang Yu, Xian-Shi Zhang, Fu-Ya Luo +4

Frame-level micro- and macro-expression spotting methods require time-consuming frame-by-frame observation during annotation. Meanwhile, video-level spotting lacks sufficient infor…

cs.CV2022★ 14 cited

Unsupervised Visual Odometry and Action Integration for PointGoal Navigation in Indoor Environment

Yijun Cao, Xianshi Zhang, Fuya Luo +2

PointGoal navigation in indoor environment is a fundamental task for personal robots to navigate to a specified point. Recent studies solved this PointGoal navigation task with nea…

cs.CV2022

Deep Pneumonia: Attention-Based Contrastive Learning for Class-Imbalanced Pneumonia Lesion Recognition in Chest X-rays

Xinxu Wei, Haohan Bai, Xianshi Zhang +1

Computer-aided X-ray pneumonia lesion recognition is important for accurate diagnosis of pneumonia. With the emergence of deep learning, the identification accuracy of pneumonia ha…

cs.CV2022★ 64 cited

Learning to Adapt to Light

Kai-Fu Yang, Cheng Cheng, Shi-Xuan Zhao +2

Light adaptation or brightness correction is a key step in improving the contrast and visual appeal of an image. There are multiple light-related tasks (for example, low-light enha…

cs.CV2021★ 16 cited

Learning Generalized Visual Odometry Using Position-Aware Optical Flow and Geometric Bundle Adjustment

Yijun Cao, Xianshi Zhang, Fuya Luo +2

Recent visual odometry (VO) methods incorporating geometric algorithm into deep-learning architecture have shown outstanding performance on the challenging monocular VO task. Despi…