About
Video Compression is a process of reducing the size of an image or video file by exploiting spatial and temporal redundancies within an image or video frame and across multiple video frames. The ultimate goal of a successful Video Compression system is to reduce data volume while retaining the perceptual quality of the decompressed data.
Source: Adversarial Video Compression Guided by Soft Edge Detection
Benchmarks
Datasets
Greatest papers with code
Compressed Video Action Recognition
CVPR 2018
• chaoyuaw/pytorch-coviar
• 
), we propose to train a deep network directly on the compressed video.
Ranked #14 on
Action Classification
on Charades
(using extra training data)
CompressAI: a PyTorch library and evaluation platform for end-to-end compression research
• InterDigitalInc/CompressAI
•
This paper presents CompressAI, a platform that provides custom operations, layers, models and tools to research, develop and evaluate end-to-end image and video compression codecs.
Semantic Perceptual Image Compression using Deep Convolution Networks
• iamaaditya/image-compression-cnn
• 
Here, we present a powerful cnn tailored to the specific task of semantic image understanding to achieve higher visual quality in lossy compression.
DVC: An End-to-end Deep Video Compression Framework
Conventional video compression approaches use the predictive coding architecture and encode the corresponding motion information and residual information.
Video Compression through Image Interpolation
ECCV 2018
• chaoyuaw/pytorch-vcii
•
An ever increasing amount of our digital communication, media consumption, and content creation revolves around videos.
Switchable Temporal Propagation Network
Our approach is based on a temporal propagation network (TPN), which models the transition-related affinity between a pair of frames in a purely data-driven manner.
A Unified End-to-End Framework for Efficient Deep Image Compression
Our EDIC method can also be readily incorporated with the Deep Video Compression (DVC) framework to further improve the video compression performance.
OpenDVC: An Open Source Implementation of the DVC Video Compression Method
At the time of writing this report, several learned video compression methods are superior to DVC, but currently none of them provides open source codes.
Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability Model
The experiments show that our approach achieves the state-of-the-art learned video compression performance in terms of both PSNR and MS-SSIM.
Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement
CVPR 2020
• RenYang-home/HLVC
•
In our HLVC approach, the hierarchical quality benefits the coding efficiency, since the high quality information facilitates the compression and enhancement of low quality frames at encoder and decoder sides, respectively.