SOTAVerified

Video Compression

Video Compression is a process of reducing the size of an image or video file by exploiting spatial and temporal redundancies within an image or video frame and across multiple video frames. The ultimate goal of a successful Video Compression system is to reduce data volume while retaining the perceptual quality of the decompressed data.

Source: Adversarial Video Compression Guided by Soft Edge Detection

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 401–425 of 496 papers

TitleStatusHype
Perceptually-inspired super-resolution of compressed videos—0
Perceptual Quality Assessment of HEVC and VVC Standards for 8K Video—0
Perceptual Video Compression with Neural Wrapping—0
Per Clip Lagrangian Multiplier Optimisation for HEVC—0
PIM: Video Coding using Perceptual Importance Maps—0
Pleno-Generation: A Scalable Generative Face Video Compression Framework with Bandwidth Intelligence—0
Plug-and-Play Versatile Compressed Video Enhancement—0
PNVC: Towards Practical INR-based Video Compression—0
Predicting total time to compress a video corpus using online inference systems—0
Prediction and Reference Quality Adaptation for Learned Video Compression—0
PromptMobile: Efficient Promptus for Low Bandwidth Mobile Video Streaming—0
Pruned Lightweight Encoders for Computer Vision—0
PS-NeRV: Patch-wise Stylized Neural Representations for Videos—0
Lossy Event Compression based on Image-derived Quad Trees and Poisson Disk Sampling—0
Quality assessment methods for perceptual video compression—0
Rate-Distortion Optimization With Alternative References For UGC Video Compression—0
Rate-Perception Optimized Preprocessing for Video Coding—0
Real-Time Object Detection and Localization in Compressive Sensed Video on Embedded Hardware—0
Real Time Object Tracking Based on Inter-frame Coding: A Review—0
Reducing The Mismatch Between Marginal and Learned Distributions in Neural Video Compression—0
Region-of-Interest Based Neural Video Compression—0
Residual Learning and Filtering Networks for End-to-End Lossless Video Compression—0
Resolution-Agnostic Neural Compression for High-Fidelity Portrait Video Conferencing via Implicit Radiance Fields—0
Rethinking Implicit Neural Representations for Vision Learners—0
Revisiting the Sample Adaptive Offset post-filter of VVC with Neural-Networks—0
Show:102550
← PrevPage 17 of 20Next →

No leaderboard results yet.