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Video Compression

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

Papers

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Showing 226–250 of 496 papers

TitleStatusHype
Dual-Bridging With Adversarial Noise Generation for Domain Adaptive rPPG Estimation—0
Complexity-Guided Slimmable Decoder for Efficient Deep Video Compression—0
Motion Information Propagation for Neural Video Compression—0
Video Compression With Entropy-Constrained Neural Representations—0
NIRVANA: Neural Implicit Representations of Videos with Adaptive Networks and Autoregressive Patch-wise ModelingCode0
FFNeRV: Flow-Guided Frame-Wise Neural Representations for VideosCode1
Scalable Hybrid Learning Techniques for Scientific Data CompressionCode1
PIM: Video Coding using Perceptual Importance Maps—0
Pruned Lightweight Encoders for Computer Vision—0
Video compression dataset and benchmark of learning-based video-quality metricsCode1
Rethinking Implicit Neural Representations for Vision Learners—0
Perceptual Video Coding for Machines via Satisfied Machine Ratio ModelingCode1
Advancing Learned Video Compression with In-loop Frame PredictionCode1
Impact of Video Compression on the Performance of Object Detection Systems for Surveillance Applications—0
The Need for Medically Aware Video Compression in Gastroenterology—0
LCCM-VC: Learned Conditional Coding Modes for Video CompressionCode0
Multi-rate adaptive transform coding for video compression—0
Efficient Cross-Modal Video Retrieval with Meta-Optimized FramesCode0
Learned Video Compression for YUV 4:2:0 Content Using Flow-based Conditional Inter-frame Coding—0
Scalable Neural Video Representations with Learnable Positional FeaturesCode1
Reducing The Mismatch Between Marginal and Learned Distributions in Neural Video Compression—0
Leveraging progressive model and overfitting for efficient learned image compression—0
Compressing Video Calls using Synthetic Talking Heads—0
Compressed Vision for Efficient Video Understanding—0
Correcting the Sub-optimal Bit Allocation—0
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