no code implementations • 24 Jul 2024 • Binzhe Li, Shurun Wang, Shiqi Wang, Yan Ye
In this paper, we pioneer to propose a variable bitrate image compression framework consisting of a pre-editing module and an end-to-end codec to achieve promising rate-accuracy performance for different LVLMs.
1 code implementation • 20 Feb 2023 • Bolin Chen, Zhao Wang, Binzhe Li, Shurun Wang, Shiqi Wang, Yan Ye
In this paper, we propose a novel framework for Interactive Face Video Coding (IFVC), which allows humans to interact with the intrinsic visual representations instead of the signals.
no code implementations • 13 Sep 2022 • Yu Tian, Zhangkai Ni, Baoliang Chen, Shurun Wang, Shiqi Wang, Hanli Wang, Sam Kwong
In particular, in order to maximum redundancy removal without impairment of robust identity information, we apply the encoder with multiple feature extraction and attention-based feature decomposition modules to progressively decompose face features into two uncorrelated components, i. e., identity and residual features, via self-supervised learning.
no code implementations • 1 Jul 2021 • Shurun Wang, Zhao Wang, Shiqi Wang, Yan Ye
In this paper, we show that the design and optimization of network architecture could be further improved for compression towards machine vision.
no code implementations • 21 Apr 2020 • Shurun Wang, Shiqi Wang, Wenhan Yang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, Wen Gao
In particular, we study the feature and texture compression in a scalable coding framework, where the base layer serves as the deep learning feature and enhancement layer targets to perfectly reconstruct the texture.
no code implementations • 10 Feb 2020 • Shurun Wang, Wenhan Yang, Shiqi Wang
In this paper, we propose a novel end-to-end feature compression scheme by leveraging the representation and learning capability of deep neural networks, towards intelligent front-end equipped analysis with promising accuracy and efficiency.
no code implementations • 14 Mar 2019 • Shurun Wang, Shiqi Wang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, Wen Gao
In this paper, we propose a scalable image compression scheme, including the base layer for feature representation and enhancement layer for texture representation.