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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 51–100 of 496 papers

TitleStatusHype
SMC++: Masked Learning of Unsupervised Video Semantic CompressionCode1
Perceptual Learned Video Compression with Recurrent Conditional GANCode1
AIM 2024 Challenge on Compressed Video Quality Assessment: Methods and ResultsCode1
BiECVC: Gated Diversification of Bidirectional Contexts for Learned Video CompressionCode1
DVC-P: Deep Video Compression with Perceptual OptimizationsCode1
Parameter-Efficient Instance-Adaptive Neural Video CompressionCode1
NeRV: Neural Representations for VideosCode1
Multi-Scale Deformable Alignment and Content-Adaptive Inference for Flexible-Rate Bi-Directional Video CompressionCode1
Neural Residual Flow Fields for Efficient Video RepresentationsCode1
CANF-VC: Conditional Augmented Normalizing Flows for Video CompressionCode1
DFPN: Deformable Frame Prediction NetworkCode1
Neural Video Compression with Diverse ContextsCode1
Deep Contextual Video CompressionCode1
ECVC: Exploiting Non-Local Correlations in Multiple Frames for Contextual Video CompressionCode1
Perceptual Quality Assessment of Face Video Compression: A Benchmark and An Effective MethodCode1
Deep Learning in Latent Space for Video Prediction and CompressionCode1
ReLaX-VQA: Residual Fragment and Layer Stack Extraction for Enhancing Video Quality AssessmentCode1
Diffusion Probabilistic Modeling for Video GenerationCode1
DVC: An End-to-end Deep Video Compression FrameworkCode1
Perceptual Quality Improvement in Videoconferencing using Keyframes-based GANCode1
CompressAI: a PyTorch library and evaluation platform for end-to-end compression researchCode1
AIM 2024 Challenge on Video Saliency Prediction: Methods and ResultsCode1
Efficient Video Compression via Content-Adaptive Super-ResolutionCode1
Perceptual Video Coding for Machines via Satisfied Machine Ratio ModelingCode1
Learning Cross-Scale Weighted Prediction for Efficient Neural Video CompressionCode1
Enhancing Quality for VVC Compressed Videos by Jointly Exploiting Spatial Details and Temporal StructureCode1
Scalable Hybrid Learning Techniques for Scientific Data CompressionCode1
Explaining Deepfake Detection by Analysing Image MatchingCode1
Advancing Learned Video Compression with In-loop Frame PredictionCode1
Neural Video Compression with Context ModulationCode0
NIRVANA: Neural Implicit Representations of Videos with Adaptive Networks and Autoregressive Patch-wise ModelingCode0
An Interactive Annotation Tool for Perceptual Video CompressionCode0
MotionAura: Generating High-Quality and Motion Consistent Videos using Discrete DiffusionCode0
BVI-CR: A Multi-View Human Dataset for Volumetric Video CompressionCode0
BVI-AOM: A New Training Dataset for Deep Video Compression OptimizationCode0
MNeRV: A Multilayer Neural Representation for VideosCode0
Neural radiance fields in the industrial and robotics domain: applications, research opportunities and use casesCode0
OpenDMC: An Open-Source Library and Performance Evaluation for Deep-learning-based Multi-frame CompressionCode0
MCUCoder: Adaptive Bitrate Learned Video Compression for IoT DevicesCode0
MGANet: A Robust Model for Quality Enhancement of Compressed VideoCode0
Listening and Seeing Again: Generative Error Correction for Audio-Visual Speech RecognitionCode0
Light Field Compression by Residual CNN Assisted JPEGCode0
Lossless compression with state space models using bits back codingCode0
DeepCache: Principled Cache for Mobile Deep VisionCode0
DeepCABAC: A Universal Compression Algorithm for Deep Neural NetworksCode0
Learned Scalable Video Coding For Humans and MachinesCode0
LCCM-VC: Learned Conditional Coding Modes for Video CompressionCode0
Learning to Compress Videos without Computing MotionCode0
CVEGAN: A Perceptually-inspired GAN for Compressed Video EnhancementCode0
Immersive Video Compression using Implicit Neural RepresentationsCode0
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