Search Results for author: Ruoyu Feng

Found 8 papers, 4 papers with code

Semantically Structured Image Compression via Irregular Group-Based Decoupling

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.

Image Compression

Prompt-ICM: A Unified Framework towards Image Coding for Machines with Task-driven Prompts

no code implementations4 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?

Inpaint Anything: Segment Anything Meets Image Inpainting

1 code implementation13 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).

Image Inpainting

HST: Hierarchical Swin Transformer for Compressed Image Super-resolution

3 code implementations21 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.

Compressed Image Super-resolution Image Super-Resolution

Image Coding for Machines with Omnipotent Feature Learning

no code implementations5 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.

Self-Supervised Learning

Semantically Video Coding: Instill Static-Dynamic Clues into Structured Bitstream for AI Tasks

no code implementations25 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.

Action Recognition object-detection +7

Cloth-Changing Person Re-identification from A Single Image with Gait Prediction and Regularization

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.

Gait Recognition Person Re-Identification

Local Patch AutoAugment with Multi-Agent Collaboration

2 code implementations20 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.

Data Augmentation Fine-Grained Image Recognition +2

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