https://github.com/circleredrain/avger
공식 코드Listening and Seeing Again: Generative Error Correction for Audio-Visual Speech Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Listening and Seeing Again: Generative Error Correction for Audio-Visual Speech Recognition
Neural Residual Flow Fields for Efficient Video Representations
MCUCoder: Adaptive Bitrate Learned Video Compression for IoT Devices
SR+Codec: a Benchmark of Super-Resolution for Video Compression Bitrate Reduction
BVI-AOM: A New Training Dataset for Deep Video Compression Optimization
BVI-CR: A Multi-View Human Dataset for Volumetric Video Compression
Enhancing HDR Video Compression through CNN-based Effective Bit Depth Adaptation
The Bjøntegaard Bible -- Why your Way of Comparing Video Codecs May Be Wrong
Image Coding for Machines with Edge Information Learning Using Segment Anything
DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks
ColorVideoVDP: A visual difference predictor for image, video and display distortions
Sandwiched Compression: Repurposing Standard Codecs with Neural Network Wrappers
I$^2$VC: A Unified Framework for Intra- & Inter-frame Video Compression
LCCM-VC: Learned Conditional Coding Modes for Video Compression
Immersive Video Compression using Implicit Neural Representations
Exploring Long- and Short-Range Temporal Information for Learned Video Compression
Semantic Perceptual Image Compression using Deep Convolution Networks
Lossless compression with state space models using bits back coding
An Interactive Annotation Tool for Perceptual Video Compression
ECVC: Exploiting Non-Local Correlations in Multiple Frames for Contextual Video Compression
VCISR: Blind Single Image Super-Resolution with Video Compression Synthetic Data
A Unified End-to-End Framework for Efficient Deep Image Compression
Bidirectional Stereo Image Compression with Cross-Dimensional Entropy Model
Perceptual Quality Improvement in Videoconferencing using Keyframes-based GAN
Dilated convolutional neural network-based deep reference picture generation for video compression
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.