zhang-yi-chi / residual-rnn
A Tensorflow implementation of the paper "Full Resolution Image Compression with Recurrent Neural Networks" (Residual RNN)
☆12Updated 6 years ago
Alternatives and similar repositories for residual-rnn:
Users that are interested in residual-rnn are comparing it to the libraries listed below
- ☆9Updated 5 years ago
- Image compression codecs benchmark inspired by Google's "Full Resolution Image Compression with Recurrent Neural Networks"☆41Updated 8 years ago
- CAE-ADMM: Implicit Bitrate Optimization via ADMM-Based Pruning in Compressive Autoencoders☆47Updated 4 years ago
- Full Resolution Image Compression with Recurrent Neural Networks in Pytorch☆8Updated 6 years ago
- Video Compression through Image Interpolation (ECCV'18) [PyTorch]☆208Updated 5 years ago
- DSSLIC: Deep Semantic Segmentation-based Layered Image Compression☆46Updated 5 years ago
- TensorFlow implementation of Conditional Probability Models for Deep Image Compression, published in CVPR 2018☆180Updated 5 years ago
- Image compression using Variational Autoencoder and Generative Adversarial Networks.☆11Updated 6 years ago
- Deep Image Compression using Decoder Side Information (ECCV 2020)☆46Updated 2 years ago
- PyTorch implementation of Full Resolution Image Compression with Recurrent Neural Networks☆193Updated 2 years ago
- ☆12Updated 5 years ago
- DSSLIC: Deep Semantic Segmentation-based Layered Image Compression☆9Updated 6 years ago
- Image Compression on COCO Dataset using Convolution AutoEncoders☆11Updated 6 years ago
- Deep generative models for distribution-preserving lossy compression☆33Updated 6 years ago
- ☆61Updated 5 years ago
- ☆168Updated 6 years ago
- Image compression☆17Updated 3 years ago
- ☆29Updated 8 years ago
- CNN Baseline for Image Compression☆10Updated 6 years ago
- The code for Channel-Level Variable Quantization Network for Deep Image Compression (IJCAI 2020)☆31Updated 3 years ago
- Designing image processing hardware and software for computer vision☆65Updated 5 years ago
- Autoencoder based image compression: can the learning be quantization independent? https://arxiv.org/abs/1802.09371☆19Updated 2 years ago
- This is the codes for paper "Learning Convolutional Networks for Content-weighted Image Compression"☆72Updated 2 years ago
- This is an implementation of a forward and reverse computational photography pipeline☆32Updated 6 years ago
- Demo Code for the paper "Joint Demosaicing and Denoising Based on Sequential Energy Minimization"☆21Updated 8 years ago
- PyTorch implementation of S-Net: A Scalable Convolutional Neural Network for JPEG Compression Artifact Reduction (2018)☆13Updated 5 years ago
- Slimmable Compressive Autoencoders for Practical Neural Image Compression☆53Updated 3 years ago
- Pytorch implementation for SRDenseNet (ICCV2017)☆68Updated 7 years ago
- ☆33Updated 8 years ago
- Official implementation of "CocoNet: A deep neural network for mapping pixel coordinates to color values" paper☆11Updated 6 years ago