Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models

26 January 2023

Papers citing "Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models"

8 / 8 papers shown

Title
Why Compress What You Can Generate? When GPT-4o Generation Ushers in Image Compression Fields Yixin Gao Xiaohan Pan X. Li Zhibo Chen 51 0 0 30 Apr 2025
PRISM-DP: Spatial Pose-based Observations for Diffusion-Policies via Segmentation, Mesh Generation, and Pose Tracking Xiatao Sun Yinxing Chen Daniel Rakita VGen 53 0 0 29 Apr 2025
DLF: Extreme Image Compression with Dual-generative Latent Fusion Naifu Xue Zhaoyang Jia Jiahao Li Bin Li Yuan Zhang Yan-Heng Lu 48 1 0 03 Mar 2025
Semantic Ensemble Loss and Latent Refinement for High-Fidelity Neural Image Compression Daxin Li Yuanchao Bai Kai Wang Junjun Jiang Xianming Liu 13 1 0 25 Jan 2024
Idempotence and Perceptual Image Compression Tongda Xu Ziran Zhu Dailan He Yanghao Li Lina Guo ... Zhe Wang Hongwei Qin Yan Wang Jingjing Liu Ya-Qin Zhang 41 14 0 17 Jan 2024
EGIC: Enhanced Low-Bit-Rate Generative Image Compression Guided by Semantic Segmentation Nikolai Korber Eduard Kromer Andreas Siebert S. Hauke Daniel Mueller-Gritschneder Björn Schuller DiffM VLM 15 4 0 06 Sep 2023
Joint Hierarchical Priors and Adaptive Spatial Resolution for Efficient Neural Image Compression Ahmed Ghorbel W. Hamidouche L. Morin 16 0 0 05 Jul 2023
End-to-end Learning of Compressible Features Saurabh Singh Sami Abu-El-Haija Nick Johnston Johannes Ballé Abhinav Shrivastava G. Toderici SSL 89 71 0 23 Jul 2020