Video Coding and Compression Technologies
82 papers on this topic
MISC: Ultra-low Bitrate Image Semantic Compression Driven by Large Multimodal Model
With the evolution of storage and communication protocols, ultra-low bitrate image compression has become a highly demanding topic. However, existing compression algorithms must sacrifice either...
Synonymous Variational Inference for Perceptual Image Compression
Recent contributions of semantic information theory reveal the set-element relationship between semantic and syntactic information, represented as synonymous relationships. In this paper, we...
VideoQA-SC: Adaptive Semantic Communication for Video Question Answering
Although semantic communication (SC) has shown its potential in efficiently transmitting multimodal data such as texts, speeches and images, SC for videos has focused primarily on pixel-level...
VidTwin: Video VAE with Decoupled Structure and Dynamics
Recent advancements in video autoencoders (Video AEs) have significantly improved the quality and efficiency of video generation. In this paper, we propose a novel and compact video autoencoder,...
GRACE: Loss-Resilient Real-Time Video through Neural Codecs
In real-time video communication, retransmitting lost packets over high-latency networks is not viable due to strict latency requirements. To counter packet losses without retransmission, two...
Multi-Scale Invertible Neural Network for Wide-Range Variable-Rate Learned Image Compression
Autoencoder-based structures have dominated recent learned image compression methods. However, the inherent information loss associated with autoencoders limits their rate-distortion performance...
Promptus: Can Prompts Streaming Replace Video Streaming with Stable Diffusion
With the exponential growth of video traffic, traditional video streaming systems are approaching their limits in compression efficiency and communication capacity. To further reduce bitrate while...
InternVQA: Advancing Compressed Video Quality Assessment with Distilling Large Foundation Model
Video quality assessment tasks rely heavily on the rich features required for video understanding, such as semantic information, texture, and temporal motion. The existing video foundational...
CompressAI: a PyTorch library and evaluation platform for end-to-end compression research
This paper presents CompressAI, a platform that provides custom operations, layers, models and tools to research, develop and evaluate end-to-end image and video compression codecs. In particular,...
Diversify, Contextualize, and Adapt: Efficient Entropy Modeling for Neural Image Codec
Designing a fast and effective entropy model is challenging but essential for practical application of neural codecs. Beyond spatial autoregressive entropy models, more efficient backward...
Generalized Nested Latent Variable Models for Lossy Coding applied to Wind Turbine Scenarios
Rate-distortion optimization through neural networks has accomplished competitive results in compression efficiency and image quality. This learning-based approach seeks to minimize the compromise...
Multiscale Point Cloud Geometry Compression
Recent years have witnessed the growth of point cloud based applications because of its realistic and fine-grained representation of 3D objects and scenes. However, it is a challenging problem to...
StreamME: Simplify 3D Gaussian Avatar within Live Stream
We propose StreamME, a method focuses on fast 3D avatar reconstruction. The StreamME synchronously records and reconstructs a head avatar from live video streams without any pre-cached data,...
AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data
The site conditions that make astronomical observatories in space and on the ground so desirable -- cold and dark -- demand a physical remoteness that leads to limited data transmission...
Towards End-to-End Image Compression and Analysis with Transformers
We propose an end-to-end image compression and analysis model with Transformers, targeting to the cloud-based image classification application. Instead of placing an existing Transformer-based...
Diff-PCC: Diffusion-based Neural Compression for 3D Point Clouds
Stable diffusion networks have emerged as a groundbreaking development for their ability to produce realistic and detailed visual content. This characteristic renders them ideal decoders, capable...
Universal Deep Image Compression via Content-Adaptive Optimization with Adapters
Deep image compression performs better than conventional codecs, such as JPEG, on natural images. However, deep image compression is learning-based and encounters a problem: the compression...
Local Compressed Video Stream Learning for Generic Event Boundary Detection
Generic event boundary detection aims to localize the generic, taxonomy-free event boundaries that segment videos into chunks. Existing methods typically require video frames to be decoded before...