168 citations · 170 across the 4 of their papers we have counts for
5 papers
Image Coding for Machines with Omnipotent Feature Learning
Ruoyu Feng, Xin Jin, Zongyu Guo +6
Image Coding for Machines (ICM) aims to compress images for AI tasks analysis rather than meeting human perception. Learning a kind of feature that is both general (for AI tasks) a…
Semantically Video Coding: Instill Static-Dynamic Clues into Structured Bitstream for AI Tasks
Xin Jin, Ruoyu Feng, Simeng Sun +3
Traditional media coding schemes typically encode image/video into a semantic-unknown binary stream, which fails to directly support downstream intelligent tasks at the bitstream l…
GraphIQA: Learning Distortion Graph Representations for Blind Image Quality Assessment
Simeng Sun, Tao Yu, Jiahua Xu +2
A good distortion representation is crucial for the success of deep blind image quality assessment (BIQA). However, most previous methods do not effectively model the relationship…
Learning Omni-frequency Region-adaptive Representations for Real Image Super-Resolution
Xin Li, Xin Jin, Tao Yu +4
Traditional single image super-resolution (SISR) methods that focus on solving single and uniform degradation (i.e., bicubic down-sampling), typically suffer from poor performance…
Multi-scale Grouped Dense Network for VVC Intra Coding
Xin Li, Simeng Sun, Zhizheng Zhang +1
Versatile Video Coding (H.266/VVC) standard achieves better image quality when keeping the same bits than any other conventional image codec, such as BPG, JPEG, and etc. However, i…