no code implementations • 16 Apr 2024 • Jixiang Luo
The burgeoning volume of digital content across diverse modalities necessitates efficient storage and retrieval methods.
no code implementations • 7 Apr 2024 • Xingtong Ge, Jixiang Luo, Xinjie Zhang, Tongda Xu, Guo Lu, Dailan He, Jing Geng, Yan Wang, Jun Zhang, Hongwei Qin
Prior research on deep video compression (DVC) for machine tasks typically necessitates training a unique codec for each specific task, mandating a dedicated decoder per task.
no code implementations • 19 Mar 2024 • Jixiang Luo, Yan Wang, Hongwei Qin
MSE-based models aim to improve objective metrics while generative models are leveraged to improve visual quality measured by subjective metrics.
no code implementations • 5 Dec 2023 • Jianghui Zhang, Yuanyuan Wang, Lina Guo, Jixiang Luo, Tongda Xu, Yan Wang, Zhi Wang, Hongwei Qin
Most image compression algorithms only consider uncompressed original image, while ignoring a large number of already existing JPEG images.
no code implementations • 25 Aug 2023 • Lina Guo, Yuanyuan Wang, Tongda Xu, Jixiang Luo, Dailan He, Zhenjun Ji, Shanshan Wang, Yang Wang, Hongwei Qin
Second, we propose pipeline parallel context model (PPCM) and compressed checkerboard context model (CCCM) for the effective conditional modeling and efficient decoding within luma and chroma components.
no code implementations • 5 Mar 2023 • Jixiang Luo, Shaohui Li, Wenrui Dai, Chenglin Li, Junni Zou, Hongkai Xiong
In this paper, we propose a novel framework for learned lossless compression of JPEG images that achieves end-to-end optimized prediction of the distribution of decoded DCT coefficients.
1 code implementation • 20 Sep 2022 • Tongda Xu, Han Gao, Chenjian Gao, Yuanyuan Wang, Dailan He, Jinyong Pi, Jixiang Luo, Ziyu Zhu, Mao Ye, Hongwei Qin, Yan Wang, Jingjing Liu, Ya-Qin Zhang
In this paper, we consider the problem of bit allocation in Neural Video Compression (NVC).
no code implementations • 29 Jul 2022 • Hongjiu Yu, Qiancheng Sun, Jin Hu, Xingyuan Xue, Jixiang Luo, Dailan He, Yilong Li, Pengbo Wang, Yuanyuan Wang, Yaxu Dai, Yan Wang, Hongwei Qin
On CPU, the latency of our implementation is comparable with JPEG XL.
1 code implementation • 28 May 2022 • Dailan He, Ziming Yang, Hongjiu Yu, Tongda Xu, Jixiang Luo, Yuan Chen, Chenjian Gao, Xinjie Shi, Hongwei Qin, Yan Wang
In the past years, learned image compression (LIC) has achieved remarkable performance.
3 code implementations • 15 May 2021 • Kecheng Chen, Jiayu Sun, Jiang Shen, Jixiang Luo, Xinyu Zhang, Xuelin Pan, Dongsheng Wu, Yue Zhao, Miguel Bento, Yazhou Ren, Xiaorong Pu
To address this issue, we propose a novel graph convolutional network-based LDCT denoising model, namely GCN-MIF, to explicitly perform multi-information fusion for denoising purpose.