https://github.com/Recognito-Vision/Linux-FaceRecognition-FaceLivenessDetection
M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection
Papers with Code 아카이브
Image Compression
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 4
- 평가표
- 11
- 보존된 평가 기록
- 22
Image Compression is an application of data compression for digital images to lower their storage and/or transmission requirements.
Source: Variable Rate Deep Image Compression With a Conditional Autoencoder
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/RenYang-home/OpenDVC
Context-adaptive Entropy Model for End-to-end Optimized Image Compression
https://github.com/ShakedDovrat/JpegArtifactRemoval
CAS-CNN: A Deep Convolutional Neural Network for Image Compression Artifact Suppression
https://github.com/TristansCloud/YellowstonesVegitiation
An End-to-End Compression Framework Based on Convolutional Neural Networks
https://github.com/USTC-IMCL/SwinIQA
SwinIQA: Learned Swin Distance for Compressed Image Quality Assessment
https://github.com/VincentChandelier/ELIC-QVRF
https://github.com/VincentChandelier/ELiC-ReImplemetation
https://github.com/VincentChandelier/GACN-QVRF
QVRF: A Quantization-error-aware Variable Rate Framework for Learned Image Compression
https://github.com/VincentChandelier/QRAF
QVRF: A Quantization-error-aware Variable Rate Framework for Learned Image Compression
https://github.com/VincentChandelier/SADN-QVRF
SADN: Learned Light Field Image Compression with Spatial-Angular Decorrelation
https://github.com/VincentChandelier/STF-QVRF
The Devil Is in the Details: Window-based Attention for Image Compression
https://github.com/Weifeng73/Zero-Shot-Super-resolution
https://github.com/WenxueCui/LapCSNet
https://github.com/XPixelGroup/BasicSR
https://github.com/YilinLiu97/Faster-DIP-Recon
https://github.com/Yuhan556/RDPC
Universal Rate-Distortion-Perception Representations for Lossy Compression
https://github.com/acse-jy220/SFC-CAE-Ready-to-use
Applying Convolutional Neural Networks to Data on Unstructured Meshes with Space-Filling Curves
https://github.com/adityassrana/Content-Weighted-Image-Compression
Learning Convolutional Networks for Content-weighted Image Compression
https://github.com/alexandru-dinu/cae
Variable Rate Image Compression with Recurrent Neural Networks
https://github.com/alterwear/arduino-firmware
https://github.com/anant95/K_means-image-compression
Semantic Perceptual Image Compression using Deep Convolution Networks
https://github.com/anushka-s/Image-restoration-using-deep-image-prior
https://github.com/aprilbian/Process-and-Forward
Process-and-Forward: Deep Joint Source-Channel Coding Over Cooperative Relay Networks
https://github.com/aprilbian/h-DJSCC
https://github.com/assafshocher/ZSSR
https://github.com/ayanglab/swinganmr
https://github.com/ayanglab/swinmr
https://github.com/benjs/DCTransformer-PyTorch
https://github.com/bestaar/predictiveFilterFlow
https://github.com/cachett/DCGANandCAE
Deep Convolutional AutoEncoder-based Lossy Image Compression
https://github.com/chxy95/hat
https://github.com/dezhao-wang/neural-syntax-code
Neural Data-Dependent Transform for Learned Image Compression
https://github.com/dniku/perceptual-gradient-networks
https://github.com/duanzhiihao/qres-vae
https://github.com/edmontdants/RNN-LSTM-GRU_Tensorflow-Hybrid-Model-Residual-GRU-ResNet-Toderici2017-CVPR
Full Resolution Image Compression with Recurrent Neural Networks
https://github.com/eyalfish/artoveq
Variable Rate Image Compression with Recurrent Neural Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.