74 citations · 99 across the 10 of their papers we have counts for
10 papers · 1 filter
Capturing Co-existing Distortions in User-Generated Content for No-reference Video Quality Assessment
Kun Yuan, Zishang Kong, Chuanchuan Zheng +2
Video Quality Assessment (VQA), which aims to predict the perceptual quality of a video, has attracted raising attention with the rapid development of streaming media technology, s…
Learning Multi-modal Representations by Watching Hundreds of Surgical Video Lectures
Kun Yuan, Vinkle Srivastav, Tong Yu +5
Recent advancements in surgical computer vision applications have been driven by vision-only models, which do not explicitly integrate the rich semantics of language into their des…
Quality-aware Pre-trained Models for Blind Image Quality Assessment
Kai Zhao, Kun Yuan, Ming Sun +2
Blind image quality assessment (BIQA) aims to automatically evaluate the perceived quality of a single image, whose performance has been improved by deep learning-based methods in…
ShowFace: Coordinated Face Inpainting with Memory-Disentangled Refinement Networks
Zhuojie Wu, Xingqun Qi, Zijian Wang +4
Face inpainting aims to complete the corrupted regions of the face images, which requires coordination between the completed areas and the non-corrupted areas. Recently, memory-ori…
Incorporating Convolution Designs into Visual Transformers
Kun Yuan, Shaopeng Guo, Ziwei Liu +3
Motivated by the success of Transformers in natural language processing (NLP) tasks, there emerge some attempts (e.g., ViT and DeiT) to apply Transformers to the vision domain. How…
Differentiable Network Adaption with Elastic Search Space
Shaopeng Guo, Yujie Wang, Kun Yuan +1
In this paper we propose a novel network adaption method called Differentiable Network Adaption (DNA), which can adapt an existing network to a specific computation budget by adjus…