Papers Video Compression
“Video Compression” 태그가 달린 논문 496편 · 필터 해제
OpenDMC: An Open-Source Library and Performance Evaluation for Deep-learning-based Multi-frame Compression
Video streaming has become an essential component of our everyday routines. Nevertheless, video data imposes a significant strain on data usage, demanding substantial bandwidth and storage resources for effective transmi…
BenchmarkingGPUVideo CompressionMultiscale Motion-Aware and Spatial-Temporal-Channel Contextual Coding Network for Learned Video Compression
Recently, learned video compression has achieved exciting performance. Following the traditional hybrid prediction coding framework, most learned methods generally adopt the motion estimation motion compensation (MEMC) m…
Motion CompensationMotion Estimationmotion predictionMS-SSIM+2Video Quality Assessment and Coding Complexity of the Versatile Video Coding Standard
In recent years, the proliferation of multimedia applications and formats, such as IPTV, Virtual Reality (VR, 360-degree), and point cloud videos, has presented new challenges to the video compression research community.…
SSIMVideo CompressionVideo Quality AssessmentEffortless Cross-Platform Video Codec: A Codebook-Based Method
Under certain circumstances, advanced neural video codecs can surpass the most complex traditional codecs in their rate-distortion (RD) performance. One of the main reasons for the high performance of existing neural vid…
Computational EfficiencyOptical Flow EstimationVideo CompressionLanguage Model Beats Diffusion -- Tokenizer is Key to Visual Generation
While Large Language Models (LLMs) are the dominant models for generative tasks in language, they do not perform as well as diffusion models on image and video generation. To effectively use LLMs for visual generation, o…
Action RecognitionImage GenerationLanguage ModelingLanguage Modelling+3High Visual-Fidelity Learned Video Compression
With the growing demand for video applications, many advanced learned video compression methods have been developed, outperforming traditional methods in terms of objective quality metrics such as PSNR. Existing methods …
Video CompressionMobileNVC: Real-time 1080p Neural Video Compression on a Mobile Device
Neural video codecs have recently become competitive with standard codecs such as HEVC in the low-delay setting. However, most neural codecs are large floating-point networks that use pixel-dense warping operations for t…
DecoderGPUMotion CompensationQuantization+1Quantum Block-Matching Algorithm using Dissimilarity Measure
Finding groups of similar image blocks within an ample search area is often necessary in different applications, such as video compression, image clustering, vector quantization, and nonlocal noise reduction. A block-mat…
ClusteringImage ClusteringQuantizationVideo CompressionIBVC: Interpolation-driven B-frame Video Compression
Learned B-frame video compression aims to adopt bi-directional motion estimation and motion compensation (MEMC) coding for middle frame reconstruction. However, previous learned approaches often directly extend neural P-…
DecoderMotion CompensationMotion EstimationOptical Flow Estimation+3Spatial-Temporal Transformer based Video Compression Framework
Learned video compression (LVC) has witnessed remarkable advancements in recent years. Similar as the traditional video coding, LVC inherits motion estimation/compensation, residual coding and other modules, all of which…
Motion EstimationPredictionVideo CompressionContext-Aware Neural Video Compression on Solar Dynamics Observatory
NASA's Solar Dynamics Observatory (SDO) mission collects large data volumes of the Sun's daily activity. Data compression is crucial for space missions to reduce data storage and video bandwidth requirements by eliminati…
Data CompressionVideo CompressionVCD: A Video Conferencing Dataset for Video Compression
Commonly used datasets for evaluating video codecs are all very high quality and not representative of video typically used in video conferencing scenarios. We present the Video Conferencing Dataset (VCD) for evaluating …
Video CompressionDesigns and Implementations in Neural Network-based Video Coding
The past decade has witnessed the huge success of deep learning in well-known artificial intelligence applications such as face recognition, autonomous driving, and large language model like ChatGPT. Recently, the applic…
Autonomous DrivingFace RecognitionLanguage ModellingLarge Language Model+1PacketGame: Multi-Stream Packet Gating for Concurrent Video Inference at Scale
The resource efficiency of video analytics workloads is critical for large-scale deployments on edge nodes and cloud clusters. Recent advanced systems have benefited from techniques including video compression, frame fil…
DecoderVideo CompressionNeural Video Compression with Temporal Layer-Adaptive Hierarchical B-frame Coding
Neural video compression (NVC) is a rapidly evolving video coding research area, with some models achieving superior coding efficiency compared to the latest video coding standard Versatile Video Coding (VVC). In convent…
Video CompressionDeep Video Codec Control for Vision Models
Standardized lossy video coding is at the core of almost all real-world video processing pipelines. Rate control is used to enable standard codecs to adapt to different network bandwidth conditions or storage constraints…
Optical Flow EstimationSemantic SegmentationVideo CompressionLSCD: A Large-Scale Screen Content Dataset for Video Compression
Multimedia compression allows us to watch videos, see pictures and hear sounds within a limited bandwidth, which helps the flourish of the internet. During the past decades, multimedia compression has achieved great succ…
Video CompressionNeural radiance fields in the industrial and robotics domain: applications, research opportunities and use cases
The proliferation of technologies, such as extended reality (XR), has increased the demand for high-quality three-dimensional (3D) graphical representations. Industrial 3D applications encompass computer-aided design (CA…
Collision AvoidanceMotion EstimationNeRFSSIM+1Self-Supervised Graph Transformer for Deepfake Detection
Deepfake detection methods have shown promising results in recognizing forgeries within a given dataset, where training and testing take place on the in-distribution dataset. However, their performance deteriorates signi…
Contrastive LearningDeepFake DetectionFace SwappingVideo CompressionConditional Residual Coding: A Remedy for Bottleneck Problems in Conditional Inter Frame Coding
Conditional coding is a new video coding paradigm enabled by neural-network-based compression. It can be shown that conditional coding is in theory better than the traditional residual coding, which is widely used in vid…
Video Compression