Papers Video Compression
“Video Compression” 태그가 달린 논문 496편 · 필터 해제
LCCM-VC: Learned Conditional Coding Modes for Video Compression
End-to-end learning-based video compression has made steady progress over the last several years. However, unlike learning-based image coding, which has already surpassed its handcrafted counterparts, learning-based vide…
Video CompressionMulti-rate adaptive transform coding for video compression
Contemporary lossy image and video coding standards rely on transform coding, the process through which pixels are mapped to an alternative representation to facilitate efficient data compression. Despite impressive perf…
Data CompressionQuantizationVideo CompressionEfficient Cross-Modal Video Retrieval with Meta-Optimized Frames
Cross-modal video retrieval aims to retrieve the semantically relevant videos given a text as a query, and is one of the fundamental tasks in Multimedia. Most of top-performing methods primarily leverage Visual Transform…
Bilevel OptimizationRetrievalVideo CompressionVideo RetrievalLearned Video Compression for YUV 4:2:0 Content Using Flow-based Conditional Inter-frame Coding
This paper proposes a learning-based video compression framework for variable-rate coding on YUV 4:2:0 content. Most existing learning-based video compression models adopt the traditional hybrid-based coding architecture…
Video CompressionScalable Neural Video Representations with Learnable Positional Features
Succinct representation of complex signals using coordinate-based neural representations (CNRs) has seen great progress, and several recent efforts focus on extending them for handling videos. Here, the main challenge is…
Video CompressionVideo Frame InterpolationVideo InpaintingVideo Super-ResolutionReducing The Mismatch Between Marginal and Learned Distributions in Neural Video Compression
During the last four years, we have witnessed the success of end-to-end trainable models for image compression. Compared to decades of incremental work, these machine learning (ML) techniques learn all the components of …
Density EstimationImage CompressionVideo CompressionLeveraging progressive model and overfitting for efficient learned image compression
Deep learning is overwhelmingly dominant in the field of computer vision and image/video processing for the last decade. However, for image and video compression, it lags behind the traditional techniques based on discre…
2kGPUImage CompressionVideo CompressionCompressing Video Calls using Synthetic Talking Heads
We leverage the modern advancements in talking head generation to propose an end-to-end system for talking head video compression. Our algorithm transmits pivot frames intermittently while the rest of the talking head vi…
Face ReenactmentTalking Head GenerationVideo CompressionCompressed Vision for Efficient Video Understanding
Experience and reasoning occur across multiple temporal scales: milliseconds, seconds, hours or days. The vast majority of computer vision research, however, still focuses on individual images or short videos lasting onl…
Video CompressionVideo UnderstandingCorrecting the Sub-optimal Bit Allocation
In this paper, we investigate the problem of bit allocation in Neural Video Compression (NVC). First, we reveal that a recent bit allocation approach claimed to be optimal is, in fact, sub-optimal due to its implementati…
Variational InferenceVideo CompressionBit Allocation using Optimization
In this paper, we consider the problem of bit allocation in Neural Video Compression (NVC). First, we reveal a fundamental relationship between bit allocation in NVC and Semi-Amortized Variational Inference (SAVI). Speci…
Variational InferenceVideo CompressionDeep Convolutional Pooling Transformer for Deepfake Detection
Recently, Deepfake has drawn considerable public attention due to security and privacy concerns in social media digital forensics. As the wildly spreading Deepfake videos on the Internet become more realistic, traditiona…
DeepFake DetectionFace SwappingVideo CompressionCross Modal Compression: Towards Human-comprehensible Semantic Compression
Traditional image/video compression aims to reduce the transmission/storage cost with signal fidelity as high as possible. However, with the increasing demand for machine analysis and semantic monitoring in recent years,…
Feature CompressionSemantic CompressionVideo CompressionB-CANF: Adaptive B-frame Coding with Conditional Augmented Normalizing Flows
Over the past few years, learning-based video compression has become an active research area. However, most works focus on P-frame coding. Learned B-frame coding is under-explored and more challenging. This work introduc…
Video CompressionWhy is the video analytics accuracy fluctuating, and what can we do about it?
It is a common practice to think of a video as a sequence of images (frames), and re-use deep neural network models that are trained only on images for similar analytics tasks on videos. In this paper, we show that this …
object-detectionObject DetectionTransfer LearningVideo CompressionExtreme-scale Talking-Face Video Upsampling with Audio-Visual Priors
In this paper, we explore an interesting question of what can be obtained from an $8\times8$ pixel video sequence. Surprisingly, it turns out to be quite a lot. We show that when we process this $8\times8$ video with the…
Super-ResolutionVideo CompressionA new way of video compression via forward-referencing using deep learning
To exploit high temporal correlations in video frames of the same scene, the current frame is predicted from the already-encoded reference frames using block-based motion estimation and compensation techniques. While thi…
Generative Adversarial NetworkMotion EstimationVideo CompressionBoosting neural video codecs by exploiting hierarchical redundancy
In video compression, coding efficiency is improved by reusing pixels from previously decoded frames via motion and residual compensation. We define two levels of hierarchical redundancy in video frames: 1) first-order: …
Video CompressionExploring Long- and Short-Range Temporal Information for Learned Video Compression
Learned video compression methods have gained a variety of interest in the video coding community since they have matched or even exceeded the rate-distortion (RD) performance of traditional video codecs. However, many c…
Motion CompensationOptical Flow EstimationVideo CompressionPS-NeRV: Patch-wise Stylized Neural Representations for Videos
We study how to represent a video with implicit neural representations (INRs). Classical INRs methods generally utilize MLPs to map input coordinates to output pixels. While some recent works have tried to directly recon…
Video CompressionVideo InpaintingVideo Reconstruction