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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 201–225 of 496 papers

TitleStatusHype
Hierarchical B-frame Video Coding Using Two-Layer CANF without Motion Coding—0
NetFlick: Adversarial Flickering Attacks on Deep Learning Based Video Compression—0
Accuracy Improvement of Object Detection in VVC Coded Video Using YOLO-v7 Features—0
Towards Scalable Neural Representation for Diverse Videos—0
Low-complexity Deep Video Compression with A Distributed Coding ArchitectureCode1
Lightweight Hybrid Video Compression Framework Using Reference-Guided Restoration Network—0
Sandwiched Video Compression: Efficiently Extending the Reach of Standard Codecs with Neural Wrappers—0
Toward Super-Resolution for Appearance-Based Gaze Estimation—0
Rate-Distortion Optimization With Alternative References For UGC Video Compression—0
Entropy Coding Improvement for Low-complexity Compressive Auto-encoders—0
Scene Matters: Model-based Deep Video Compression—0
Geometry-based spherical JND modeling for 360^ display—0
Butterfly: Multiple Reference Frames Feature Propagation Mechanism for Neural Video Compression—0
RQAT-INR: Improved Implicit Neural Image Compression—0
The First Comprehensive Dataset with Multiple Distortion Types for Visual Just-Noticeable Differences—0
Neural Video Compression with Diverse ContextsCode1
Leveraging Video Coding Knowledge for Deep Video Enhancement—0
Content-Adaptive Motion Rate Adaption for Learned Video Compression—0
Rate-Perception Optimized Preprocessing for Video Coding—0
Differentiable bit-rate estimation for neural-based video codec enhancement—0
Optimized learned entropy coding parameters for practical neural-based image and video compression—0
Learning to Compress Unmanned Aerial Vehicle (UAV) Captured Video: Benchmark and Analysis—0
Analysis of displacement compensation methods for wavelet lifting of medical 3-D thorax CT volume data—0
Contactless Pulse Estimation Leveraging Pseudo Labels and Self-Supervision—0
Non-Semantics Suppressed Mask Learning for Unsupervised Video Semantic CompressionCode1
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