Recommend resources

Resources (ours):
https://github.com/tongdaxu/Bit-Allocation-Using-Optimization (Our ICML 2023)
https://github.com/topriss/ILVC_RI (Our NeurIPS 2023)
https://github.com/tongdaxu/Idempotence-and-Perceptual-Image-Compression （Our ICLR 2024）
https://github.com/xyzysz/Bandwidth_efficient_nic (Our ICASSP 2024)
https://github.com/tongdaxu/pytorch-improving-inference-for-neural-image-compression
https://github.com/tongdaxu/YAECL-Yet-Another-Entropy-Coding-Library
more to come

Recommended Resources
https://github.com/tensorflow/compression
https://github.com/google/codex
https://github.com/InterDigitalInc/CompressAI
https://github.com/facebookresearch/NeuralCompression
https://github.com/JiangWeibeta/Checkerboard-Context-Model-for-Efficient-Learned-Image-Compression (Reproduction of our CVPR 2021 paper checkerboard)
https://github.com/VincentChandelier/ELiC-ReImplemetation (PyTorch Reproduction of our CVPR 2022 paper ELIC)
https://github.com/Nikolai10/ELIC (TensorFlow Reproduction of our CVPR 2022 paper ELIC)
https://github.com/microsoft/DCVC