activity
20182022
most citedLearning Texture Transformer Network for Image Super-Resolution

47 citations · 82 across the 4 of their papers we have counts for

collaborators

11 papers

cs.CV20222 cited

Fine-Grained Image Style Transfer with Visual Transformers

Jianbo Wang, Huan Yang, Jianlong Fu +2

With the development of the convolutional neural network, image style transfer has drawn increasing attention. However, most existing approaches adopt a global feature transformati…

cs.CV20229 cited

AI Illustrator: Translating Raw Descriptions into Images by Prompt-based Cross-Modal Generation

Yiyang Ma, Huan Yang, Bei Liu +2

AI illustrator aims to automatically design visually appealing images for books to provoke rich thoughts and emotions. To achieve this goal, we propose a framework for translating…

eess.IV20221 cited

4D LUT: Learnable Context-Aware 4D Lookup Table for Image Enhancement

Chengxu Liu, Huan Yang, Jianlong Fu +1

Image enhancement aims at improving the aesthetic visual quality of photos by retouching the color and tone, and is an essential technology for professional digital photography. Re…

eess.IV20226 cited

Learning Trajectory-Aware Transformer for Video Super-Resolution

Chengxu Liu, Huan Yang, Jianlong Fu +1

Video super-resolution (VSR) aims to restore a sequence of high-resolution (HR) frames from their low-resolution (LR) counterparts. Although some progress has been made, there are…

cs.CV2021

Learning Fine-Grained Motion Embedding for Landscape Animation

Hongwei Xue, Bei Liu, Huan Yang +3

In this paper we focus on landscape animation, which aims to generate time-lapse videos from a single landscape image. Motion is crucial for landscape animation as it determines ho…

eess.IV20211 cited

Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment

Heliang Zheng, Huan Yang, Jianlong Fu +2

An important scenario for image quality assessment (IQA) is to evaluate image restoration (IR) algorithms. The state-of-the-art approaches adopt a full-reference paradigm that comp…