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Seeking Subjectivity in Visual Emotion Distribution Learning
Jingyuan Yang, Jie Li, Leida Li +3
Visual Emotion Analysis (VEA), which aims to predict people's emotions towards different visual stimuli, has become an attractive research topic recently. Rather than a single labe…
SOLVER: Scene-Object Interrelated Visual Emotion Reasoning Network
Jingyuan Yang, Xinbo Gao, Leida Li +2
Visual Emotion Analysis (VEA) aims at finding out how people feel emotionally towards different visual stimuli, which has attracted great attention recently with the prevalence of…
Stimuli-Aware Visual Emotion Analysis
Jingyuan Yang, Jie Li, Xiumei Wang +2
Visual emotion analysis (VEA) has attracted great attention recently, due to the increasing tendency of expressing and understanding emotions through images on social networks. Dif…
A Circular-Structured Representation for Visual Emotion Distribution Learning
Jingyuan Yang, Jie Li, Leida Li +2
Visual Emotion Analysis (VEA) has attracted increasing attention recently with the prevalence of sharing images on social networks. Since human emotions are ambiguous and subjectiv…
Image Fine-grained Inpainting
Zheng Hui, Jie Li, Xiumei Wang +1
Image inpainting techniques have shown promising improvement with the assistance of generative adversarial networks (GANs) recently. However, most of them often suffered from compl…
Progressive Perception-Oriented Network for Single Image Super-Resolution
Zheng Hui, Jie Li, Xinbo Gao +1
Recently, it has been demonstrated that deep neural networks can significantly improve the performance of single image super-resolution (SISR). Numerous studies have concentrated o…
PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report
Andrey Ignatov, Radu Timofte, Thang Van Vu +45
This paper reviews the first challenge on efficient perceptual image enhancement with the focus on deploying deep learning models on smartphones. The challenge consisted of two tra…
Fast and Accurate Single Image Super-Resolution via Information Distillation Network
Zheng Hui, Xiumei Wang, Xinbo Gao
Recently, deep convolutional neural networks (CNNs) have been demonstrated remarkable progress on single image super-resolution. However, as the depth and width of the networks inc…