no code implementations • ICCV 2023 • Ruoyu Feng, Yixin Gao, Xin Jin, Runsen Feng, Zhibo Chen
Nevertheless, they divide the input image into multiple rectangular regions according to semantics and ignore avoiding information interaction among them, causing waste of bitrate and distorted reconstruction of region boundaries.
no code implementations • 4 May 2023 • Ruoyu Feng, Jinming Liu, Xin Jin, Xiaohan Pan, Heming Sun, Zhibo Chen
For ICM, developing a unified codec to reduce information redundancy while empowering the compressed features to support various vision tasks is very important, which inevitably faces two core challenges: 1) How should the compression strategy be adjusted based on the downstream tasks?
1 code implementation • 13 Apr 2023 • Tao Yu, Runseng Feng, Ruoyu Feng, Jinming Liu, Xin Jin, Wenjun Zeng, Zhibo Chen
We are also very willing to help everyone share and promote new projects based on our Inpaint Anything (IA).
3 code implementations • 21 Aug 2022 • Bingchen Li, Xin Li, Yiting Lu, Sen Liu, Ruoyu Feng, Zhibo Chen
Compressed Image Super-resolution has achieved great attention in recent years, where images are degraded with compression artifacts and low-resolution artifacts.
Ranked #1 on
Compressed Image Super-resolution
on DIV2K-q40-x4
no code implementations • 5 Jul 2022 • Ruoyu Feng, Xin Jin, Zongyu Guo, Runsen Feng, Yixin Gao, Tianyu He, Zhizheng Zhang, Simeng Sun, Zhibo Chen
Learning a kind of feature that is both general (for AI tasks) and compact (for compression) is pivotal for its success.
no code implementations • 25 Jan 2022 • Xin Jin, Ruoyu Feng, Simeng Sun, Runsen Feng, Tianyu He, Zhibo Chen
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 level.
1 code implementation • CVPR 2022 • Xin Jin, Tianyu He, Kecheng Zheng, Zhiheng Yin, Xu Shen, Zhen Huang, Ruoyu Feng, Jianqiang Huang, Xian-Sheng Hua, Zhibo Chen
Specifically, we introduce Gait recognition as an auxiliary task to drive the Image ReID model to learn cloth-agnostic representations by leveraging personal unique and cloth-independent gait information, we name this framework as GI-ReID.
Ranked #5 on
Person Re-Identification
on PRCC
2 code implementations • 20 Mar 2021 • Shiqi Lin, Tao Yu, Ruoyu Feng, Xin Li, Xin Jin, Zhibo Chen
We formulate it as a multi-agent reinforcement learning (MARL) problem, where each agent learns an augmentation policy for each patch based on its content together with the semantics of the whole image.