1 code implementation • 24 May 2024 • Shiyu Qin, Jinpeng Wang, Yimin Zhou, Bin Chen, Tianci Luo, Baoyi An, Tao Dai, Shutao Xia, YaoWei Wang
Learned visual compression is an important and active task in multimedia.
no code implementations • 23 Jan 2024 • Xiang Liu, Jiahong Chen, Bin Chen, Zimo Liu, Baoyi An, Shu-Tao Xia
With different parameter settings, our method can outperform popular AE-based codecs in constrained environments in terms of both quality and decoding time, or achieve state-of-the-art reconstruction quality compared to other INR codecs.
no code implementations • 19 Jan 2024 • Yujun Huang, Bin Chen, Naiqi Li, Baoyi An, Shu-Tao Xia, YaoWei Wang
In this paper, we propose a Measurement-Bounds-based Rate-Adaptive Image Compressed Sensing Network (MB-RACS) framework, which aims to adaptively determine the sampling rate for each image block in accordance with traditional measurement bounds theory.
no code implementations • 23 Nov 2023 • Shiyu Qin, Bin Chen, Yujun Huang, Baoyi An, Tao Dai, Shu-Tao Xia
The explosion of data has resulted in more and more associated text being transmitted along with images.
no code implementations • 23 Nov 2023 • Shiyu Qin, Yimin Zhou, Jinpeng Wang, Bin Chen, Baoyi An, Tao Dai, Shu-Tao Xia
In this paper, we propose a progressive learning paradigm for transformer-based variable-rate image compression.