Papers Video Compression
“Video Compression” 태그가 달린 논문 496편 · 필터 해제
Machine vision-aware quality metrics for compressed image and video assessment
A main goal in developing video-compression algorithms is to enhance human-perceived visual quality while maintaining file size. But modern video-analysis efforts such as detection and recognition, which are integral to …
Autonomous VehiclesVideo CompressionHigh-Frequency Enhanced Hybrid Neural Representation for Video Compression
Neural Representations for Videos (NeRV) have simplified the video codec process and achieved swift decoding speeds by encoding video content into a neural network, presenting a promising solution for video compression. …
DecoderVideo CompressionThe evolution of volumetric video: A survey of smart transcoding and compression approaches
Volumetric video, the capture and display of three-dimensional (3D) imagery, has emerged as a revolutionary technology poised to transform the media landscape, enabling immersive experiences that transcend the limitation…
Video CompressionRadiance Field Delta Video Compression in Edge-Enabled Vehicular Metaverse
Connected and autonomous vehicles (CAVs) offload computationally intensive tasks to multi-access edge computing (MEC) servers via vehicle-to-infrastructure (V2I) communication, enabling applications within the vehicular …
Autonomous VehiclesDecoderEdge-computingSSIM+1DMVC: Multi-Camera Video Compression Network aimed at Improving Deep Learning Accuracy
We introduce a cutting-edge video compression framework tailored for the age of ubiquitous video data, uniquely designed to serve machine learning applications. Unlike traditional compression methods that prioritize huma…
Data CompressionVideo CompressionPredicting total time to compress a video corpus using online inference systems
Predicting the computational cost of compressing/transcoding clips in a video corpus is important for resource management of cloud services and VOD (Video On Demand) providers. Currently, customers of cloud video service…
Video CompressionStandardizing Generative Face Video Compression using Supplemental Enhancement Information
This paper proposes a Generative Face Video Compression (GFVC) approach using Supplemental Enhancement Information (SEI), where a series of compact spatial and temporal representations of a face video signal (i.e., 2D/3D…
Video CompressionGenerative Human Video Compression with Multi-granularity Temporal Trajectory Factorization
In this paper, we propose a novel Multi-granularity Temporal Trajectory Factorization framework for generative human video compression, which holds great potential for bandwidth-constrained human-centric video communicat…
Video CompressionCompressing Scene Dynamics: A Generative Approach
This paper proposes to learn generative priors from the motion patterns instead of video contents for generative video compression. The priors are derived from small motion dynamics in common scenes such as swinging tree…
DecoderVideo CompressionECVC: Exploiting Non-Local Correlations in Multiple Frames for Contextual Video Compression
In Learned Video Compression (LVC), improving inter prediction, such as enhancing temporal context mining and mitigating accumulated errors, is crucial for boosting rate-distortion performance. Existing LVCs mainly focus…
Video CompressionBeyond GFVC: A Progressive Face Video Compression Framework with Adaptive Visual Tokens
Recently, deep generative models have greatly advanced the progress of face video coding towards promising rate-distortion performance and diverse application functionalities. Beyond traditional hybrid video coding parad…
Motion EstimationPhilosophyVideo CompressionFast Data-independent KLT Approximations Based on Integer Functions
The Karhunen-Lo\`eve transform (KLT) stands as a well-established discrete transform, demonstrating optimal characteristics in data decorrelation and dimensionality reduction. Its ability to condense energy compression i…
Dimensionality ReductionImage CompressionVideo CompressionMotionAura: Generating High-Quality and Motion Consistent Videos using Discrete Diffusion
The spatio-temporal complexity of video data presents significant challenges in tasks such as compression, generation, and inpainting. We present four key contributions to address the challenges of spatiotemporal video p…
Denoisingparameter-efficient fine-tuningQuantizationText-to-Video Generation+3High-Efficiency Neural Video Compression via Hierarchical Predictive Learning
The enhanced Deep Hierarchical Video Compression-DHVC 2.0-has been introduced. This single-model neural video codec operates across a broad range of bitrates, delivering not only superior compression performance to repre…
Motion EstimationVideo CompressionReleasing the Parameter Latency of Neural Representation for High-Efficiency Video Compression
For decades, video compression technology has been a prominent research area. Traditional hybrid video compression framework and end-to-end frameworks continue to explore various intra- and inter-frame reference and pred…
Video CompressionFast Encoding and Decoding for Implicit Video Representation
Despite the abundant availability and content richness for video data, its high-dimensionality poses challenges for video research. Recent advancements have explored the implicit representation for videos using neural ne…
DecoderVideo CompressionNeural Video Representation for Redundancy Reduction and Consistency Preservation
Implicit neural representation (INR) embed various signals into neural networks. They have gained attention in recent years because of their versatility in handling diverse signal types. In the context of video, INR achi…
Video CompressionAIM 2024 Challenge on Video Saliency Prediction: Methods and Results
This paper reviews the Challenge on Video Saliency Prediction at AIM 2024. The goal of the participants was to develop a method for predicting accurate saliency maps for the provided set of video sequences. Saliency maps…
Saliency DetectionSaliency PredictionVideo CompressionVideo Saliency Detection+1Multi-Scale Feature Prediction with Auxiliary-Info for Neural Image Compression
Recently, significant improvements in rate-distortion performance of image compression have been achieved with deep-learning techniques. A key factor in this success is the use of additional bits to predict an approximat…
Image Compressionparameter estimationVideo CompressionThe Practice of Averaging Rate-Distortion Curves over Testsets to Compare Learned Video Codecs Can Cause Misleading Conclusions
This paper aims to demonstrate how the prevalent practice in the learned video compression community of averaging rate-distortion (RD) curves across a test video set can lead to misleading conclusions in evaluating codec…
Video Compression