no code implementations • 16 Aug 2024 • Jinming Liu, Yuntao Wei, Junyan Lin, Shengyang Zhao, Heming Sun, Zhibo Chen, Wenjun Zeng, Xin Jin
We present a new image compression paradigm to achieve ``intelligently coding for machine'' by cleverly leveraging the common sense of Large Multimodal Models (LMMs).
no code implementations • 23 May 2024 • Zhibo Chen, Heming Sun, Li Zhang, Fan Zhang
This paper provides a survey of the latest developments in visual signal coding and processing with generative models.
no code implementations • 18 Jan 2024 • Tianyu Zhu, Heming Sun, Xiankui Xiong, Xuanpeng Zhu, Yong Gong, Minge jing, Yibo Fan
Our experiments compare the effects of different dimensions such as attack methods, models, qualities, and targets, concluding that in the worst case, there is a 61. 55% decrease in PSNR or a 19. 15 times increase in bpp under the PGD attack.
no code implementations • 5 Dec 2023 • Tianhao Peng, Ge Gao, Heming Sun, Fan Zhang, David Bull
In recent years, end-to-end learnt video codecs have demonstrated their potential to compete with conventional coding algorithms in term of compression efficiency.
no code implementations • 24 Aug 2023 • Ao Luo, Linxin Song, Keisuke Nonaka, Kyohei Unno, Heming Sun, Masayuki Goto, Jiro Katto
In recent years, the task of learned point cloud compression has gained prominence.
no code implementations • 4 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?
2 code implementations • CVPR 2023 • Jinming Liu, Heming Sun, Jiro Katto
Most existing LIC methods are Convolutional Neural Networks-based (CNN-based) or Transformer-based, which have different advantages.
Ranked #1 on Image Compression on kodak
1 code implementation • 18 Feb 2023 • Fangzheng Lin, Heming Sun, Jinming Liu, Jiro Katto
The proposed method features a comparable decoding speed to Checkerboard while reaching the RD performance of Autoregressive and even also outperforming Autoregressive.
no code implementations • 12 Nov 2022 • Shota Hirose, Shiori Maki, Naoki Wada, Heming Sun, Jiro Katto
Spectral Normalization is one of the best methods for stabilizing the training of Generative Adversarial Network.
no code implementations • 3 Sep 2022 • Jinming Liu, Heming Sun, Jiro Katto
Most machine vision tasks (e. g., semantic segmentation) are based on images encoded and decoded by image compression algorithms (e. g., JPEG).
no code implementations • 30 Aug 2022 • Ran Wang, Jinming Liu, Heming Sun, Jiro Katto
Lossless image compression is an essential research field in image compression.
1 code implementation • 2 Aug 2022 • Fangzheng Lin, Heming Sun, Jiro Katto
Learned image compression allows achieving state-of-the-art accuracy and compression ratios, but their relatively slow runtime performance limits their usage.
no code implementations • 21 Jun 2022 • Ao Luo, Heming Sun, Jinming Liu, Jiro Katto
Learned Image Compression (LIC) gradually became more and more famous in these years.
no code implementations • 28 May 2022 • Heming Sun, Lu Yu, Jiro Katto
Learned image compression (LIC) has reached a comparable coding gain with traditional hand-crafted methods such as VVC intra.
no code implementations • 17 Nov 2021 • Heming Sun, Lu Yu, Jiro Katto
To our best knowledge, this is the first work to give a complete analysis on the coding gain and the memory cost for a quantized LIC network, which validates the feasibility of the hardware implementation.
no code implementations • 31 Oct 2021 • Zhao Zan, Chao Liu, Heming Sun, Xiaoyang Zeng, Yibo Fan
Learned image compression techniques have achieved considerable development in recent years.
1 code implementation • 19 Aug 2021 • Chao Liu, Heming Sun, Jiro Katto, Xiaoyang Zeng, Yibo Fan
To reduce the complexity, a light ResNet structure is used as the backbone for both RP-Net and LF-Net.
1 code implementation • 5 Aug 2021 • Heming Sun, Lu Yu, Jiro Katto
As far as we know, this is the first work to explore a fully NM based framework for intra prediction, and we reach a better coding gain with a lower complexity compared with the previous work.
no code implementations • 25 Oct 2020 • Chao Liu, Heming Sun, Jiro Katto, Xiaoyang Zeng, Yibo Fan
Convolutional neural network (CNN)-based filters have achieved great success in video coding.
1 code implementation • EMNLP 2021 • Xinliang Frederick Zhang, Heming Sun, Xiang Yue, Simon Lin, Huan Sun
For evaluation, we introduce Query Bank and Relevance Set, where the former contains 1, 236 human-paraphrased queries while the latter contains ~32 human-annotated FAQ items for each query.
3 code implementations • 6 Jan 2020 • Zhengxue Cheng, Heming Sun, Masaru Takeuchi, Jiro Katto
In this paper, we explore the remaining redundancy of recent learned compression algorithms.
no code implementations • 22 Nov 2019 • Chao Liu, Heming Sun, Junan Chen, Zhengxue Cheng, Masaru Takeuchi, Jiro Katto, Xiaoyang Zeng, Yibo Fan
This method is mainly composed of two parts: intra prediction and reconstruction filtering.
no code implementations • CVPR 2019 • Zhengxue Cheng, Heming Sun, Masaru Takeuchi, Jiro Katto
Experimental results demonstrate that our proposed image compression outperforms the latest image compression standard with MS-SSIM quality metric, and provides higher performance compared with state-of-the-art learning compression methods at high bit rates, which benefits from our spatial energy compaction approach.
no code implementations • 1 Jul 2018 • Zhengxue Cheng, Heming Sun, Masaru Takeuchi, Jiro Katto
Image compression has been investigated for many decades.
1 code implementation • 25 Apr 2018 • Zhengxue Cheng, Heming Sun, Masaru Takeuchi, Jiro Katto
Image compression has been investigated as a fundamental research topic for many decades.