Papers Video Compression
“Video Compression” 태그가 달린 논문 496편 · 필터 해제
Hierarchical B-frame Video Coding Using Two-Layer CANF without Motion Coding
Typical video compression systems consist of two main modules: motion coding and residual coding. This general architecture is adopted by classical coding schemes (such as international standards H.265 and H.266) and dee…
Video CompressionNetFlick: Adversarial Flickering Attacks on Deep Learning Based Video Compression
Video compression plays a significant role in IoT devices for the efficient transport of visual data while satisfying all underlying bandwidth constraints. Deep learning-based video compression methods are rapidly replac…
Deep LearningVideo ClassificationVideo CompressionAccuracy Improvement of Object Detection in VVC Coded Video Using YOLO-v7 Features
With advances in image recognition technology based on deep learning, automatic video analysis by Artificial Intelligence is becoming more widespread. As the amount of video used for image recognition increases, efficien…
Objectobject-detectionObject DetectionVideo CompressionTowards Scalable Neural Representation for Diverse Videos
Implicit neural representations (INR) have gained increasing attention in representing 3D scenes and images, and have been recently applied to encode videos (e.g., NeRV, E-NeRV). While achieving promising results, existi…
Action RecognitionVideo CompressionLow-complexity Deep Video Compression with A Distributed Coding Architecture
Prevalent predictive coding-based video compression methods rely on a heavy encoder to reduce temporal redundancy, which makes it challenging to deploy them on resource-constrained devices. Since the 1970s, distributed s…
DecoderMotion EstimationVideo CompressionLightweight Hybrid Video Compression Framework Using Reference-Guided Restoration Network
Recent deep-learning-based video compression methods brought coding gains over conventional codecs such as AVC and HEVC. However, learning-based codecs generally require considerable computation time and model complexity…
DecoderVideo CompressionSandwiched Video Compression: Efficiently Extending the Reach of Standard Codecs with Neural Wrappers
We propose sandwiched video compression -- a video compression system that wraps neural networks around a standard video codec. The sandwich framework consists of a neural pre- and post-processor with a standard video co…
Motion CompensationVideo CompressionToward Super-Resolution for Appearance-Based Gaze Estimation
Gaze tracking is a valuable tool with a broad range of applications in various fields, including medicine, psychology, virtual reality, marketing, and safety. Therefore, it is essential to have gaze tracking software tha…
Gaze EstimationGaze PredictionMarketingSelf-Supervised Learning+2Rate-Distortion Optimization With Alternative References For UGC Video Compression
User generated content (UGC) refers to videos that are uploaded by users and shared over the Internet. UGC may have low quality due to noise and previous compression. When re-encoding UGC for streaming or downloading, a …
Video CompressionEntropy Coding Improvement for Low-complexity Compressive Auto-encoders
End-to-end image and video compression using auto-encoders (AE) offers new appealing perspectives in terms of rate-distortion gains and applications. While most complex models are on par with the latest compression stand…
QuantizationVideo CompressionScene Matters: Model-based Deep Video Compression
Video compression has always been a popular research area, where many traditional and deep video compression methods have been proposed. These methods typically rely on signal prediction theory to enhance compression per…
modelVideo CompressionGeometry-based spherical JND modeling for 360$^\circ$ display
360$^\circ$ videos have received widespread attention due to its realistic and immersive experiences for users. To date, how to accurately model the user perceptions on 360$^\circ$ display is still a challenging issue. I…
Video CompressionRQAT-INR: Improved Implicit Neural Image Compression
Deep variational autoencoders for image and video compression have gained significant attraction in the recent years, due to their potential to offer competitive or better compression rates compared to the decades long t…
Image CompressionVideo CompressionButterfly: Multiple Reference Frames Feature Propagation Mechanism for Neural Video Compression
Using more reference frames can significantly improve the compression efficiency in neural video compression. However, in low-latency scenarios, most existing neural video compression frameworks usually use the previous …
Video CompressionThe First Comprehensive Dataset with Multiple Distortion Types for Visual Just-Noticeable Differences
Recently, with the development of deep learning, a number of Just Noticeable Difference (JND) datasets have been built for JND modeling. However, all the existing JND datasets only label the JND points based on the level…
Image Quality AssessmentVideo CompressionNeural Video Compression with Diverse Contexts
For any video codecs, the coding efficiency highly relies on whether the current signal to be encoded can find the relevant contexts from the previous reconstructed signals. Traditional codec has verified more contexts b…
DiversityOptical Flow EstimationVideo CompressionLeveraging Video Coding Knowledge for Deep Video Enhancement
Recent advancements in deep learning techniques have significantly improved the quality of compressed videos. However, previous approaches have not fully exploited the motion characteristics of compressed videos, such as…
Video CompressionVideo EnhancementVideo RestorationContent-Adaptive Motion Rate Adaption for Learned Video Compression
This paper introduces an online motion rate adaptation scheme for learned video compression, with the aim of achieving content-adaptive coding on individual test sequences to mitigate the domain gap between training and …
Video CompressionRate-Perception Optimized Preprocessing for Video Coding
In the past decades, lots of progress have been done in the video compression field including traditional video codec and learning-based video codec. However, few studies focus on using preprocessing techniques to improv…
Image Quality AssessmentVideo CompressionDifferentiable bit-rate estimation for neural-based video codec enhancement
Neural networks (NN) can improve standard video compression by pre- and post-processing the encoded video. For optimal NN training, the standard codec needs to be replaced with a codec proxy that can provide derivatives …
Video Compression