SOTAVerified

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 51–75 of 496 papers

TitleStatusHype
DVC-P: Deep Video Compression with Perceptual OptimizationsCode1
OpenDVC: An Open Source Implementation of the DVC Video Compression MethodCode1
Perceptual Quality Assessment of Face Video Compression: A Benchmark and An Effective MethodCode1
Perceptual Quality Improvement in Videoconferencing using Keyframes-based GANCode1
Enhancing Quality for VVC Compressed Videos by Jointly Exploiting Spatial Details and Temporal StructureCode1
Rethinking Video Tokenization: A Conditioned Diffusion-based ApproachCode1
Scalable Hybrid Learning Techniques for Scientific Data CompressionCode1
Scalable Neural Video Representations with Learnable Positional FeaturesCode1
Perceptual Video Coding for Machines via Satisfied Machine Ratio ModelingCode1
CANF-VC: Conditional Augmented Normalizing Flows for Video CompressionCode1
The Bjøntegaard Bible -- Why your Way of Comparing Video Codecs May Be WrongCode1
Deep Learning in Latent Space for Video Prediction and CompressionCode1
DFPN: Deformable Frame Prediction NetworkCode1
Coordinate-Aware Modulation for Neural FieldsCode1
Convolutional Tensor-Train LSTM for Spatio-temporal LearningCode1
Deep Contextual Video CompressionCode1
AIM 2024 Challenge on Compressed Video Quality Assessment: Methods and ResultsCode1
DVC: An End-to-end Deep Video Compression FrameworkCode1
ECVC: Exploiting Non-Local Correlations in Multiple Frames for Contextual Video CompressionCode1
Efficient Video Compression via Content-Adaptive Super-ResolutionCode1
Diffusion Probabilistic Modeling for Video GenerationCode1
AIM 2024 Challenge on Video Saliency Prediction: Methods and ResultsCode1
FFNeRV: Flow-Guided Frame-Wise Neural Representations for VideosCode1
Flexible-Rate Learned Hierarchical Bi-Directional Video Compression With Motion Refinement and Frame-Level Bit AllocationCode1
Explaining Deepfake Detection by Analysing Image MatchingCode1
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