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20212026
most citedToward Better SSIM Loss for Unsupervised Monocular Depth Estimation

5 citations · 6 across the 4 of their papers we have counts for

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cs.CV2026

Bio-inspired Color Constancy: From Gray Anchoring Theory to Gray Pixel Methods

Kai-Fu Yang, Fu-Ya Luo, Yong-Jie Li

Color constancy is a fundamental ability of many biological visual systems and a crucial step in computer imaging systems. Bio-inspired modeling offers a promising way to elucidate…

cs.CV20255 cited

Toward Better SSIM Loss for Unsupervised Monocular Depth Estimation

Yijun Cao, Fuya Luo, Yongjie Li

Unsupervised monocular depth learning generally relies on the photometric relation among temporally adjacent images. Most of previous works use both mean absolute error (MAE) and s…

cs.CV20241 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.CV2023

Nighttime Thermal Infrared Image Colorization with Feedback-based Object Appearance Learning

Fu-Ya Luo, Shu-Lin Liu, Yi-Jun Cao +4

Stable imaging in adverse environments (e.g., total darkness) makes thermal infrared (TIR) cameras a prevalent option for night scene perception. However, the low contrast and lack…

cs.CV2021

Thermal Infrared Image Colorization for Nighttime Driving Scenes with Top-Down Guided Attention

Fuya Luo, Yunhan Li, Guang Zeng +3

Benefitting from insensitivity to light and high penetration of foggy environments, infrared cameras are widely used for sensing in nighttime traffic scenes. However, the low contr…