1 code implementation • 20 Jul 2023 • Zhenghui Zhao, Lixiang Ru, Chen Wu
Specifically, change missing refer to the situation that the WSCD model fails to predict any changed pixels, even though the image-level label indicates changed, and vice versa for change fabricating.
no code implementations • 6 Apr 2023 • Zhao Zan, Leilei Huang, Shushi Chen, Xiantao Zhang, Zhenghui Zhao, Haibing Yin, Yibo Fan
Experimental results demonstrate that our solution outperforms the state-of-the-art works with a complexity reduction of 44. 74% to 68. 76% and a BD-BR increase of 0. 60% to 2. 33%.
no code implementations • 12 Mar 2021 • Jianhui Chang, Zhenghui Zhao, Lingbo Yang, Chuanmin Jia, Jian Zhang, Siwei Ma
To this end, we propose a novel end-to-end semantic prior modeling-based conceptual coding scheme towards extremely low bitrate image compression, which leverages semantic-wise deep representations as a unified prior for entropy estimation and texture synthesis.
2 code implementations • 10 Nov 2020 • Jianhui Chang, Zhenghui Zhao, Chuanmin Jia, Shiqi Wang, Lingbo Yang, Qi Mao, Jian Zhang, Siwei Ma
To this end, we propose a novel conceptual compression framework that encodes visual data into compact structure and texture representations, then decodes in a deep synthesis fashion, aiming to achieve better visual reconstruction quality, flexible content manipulation, and potential support for various vision tasks.
no code implementations • 7 Apr 2019 • Siwei Ma, Xinfeng Zhang, Chuanmin Jia, Zhenghui Zhao, Shiqi Wang, Shanshe Wang
Deep convolution neural network (CNN) which makes the neural network resurge in recent years and has achieved great success in both artificial intelligent and signal processing fields, also provides a novel and promising solution for image and video compression.