Papers with Code 아카이브
1 Image, 2*2 Stitchi
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 12
- 평가표
- 1
- 보존된 평가 기록
- 1
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Lornatang/ESRGAN-PyTorch
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/Lornatang/FSRCNN-PyTorch
https://github.com/Lornatang/PyTorch-CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/Lornatang/SRCNN-PyTorch
https://github.com/Lornatang/VDSR-PyTorch
Accurate Image Super-Resolution Using Very Deep Convolutional Networks
https://github.com/LouieYang/deep-photo-styletransfer-tf
https://github.com/LouieYang/stroke-controllable-fast-style-transfer
Stroke Controllable Fast Style Transfer with Adaptive Receptive Fields
https://github.com/Lu-Hsuan/A-Neural-Algorithm-of-Artistic-Style
https://github.com/LucasSheng/avatar-net
Avatar-Net: Multi-scale Zero-shot Style Transfer by Feature Decoration
https://github.com/LynnHo/CycleGAN-Tensorflow-2
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/LynnHo/CycleGAN-Tensorflow-PyTorch-Simple
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/M-Usman10/DenseSqueeze-RCNN
https://github.com/MIC-DKFZ/DetectionAndRegression
https://github.com/MIC-DKFZ/RegRCNN
https://github.com/MIT-HAN-LAB/temporal-shift-module
https://github.com/MIT-SPARK/GNC-and-ADAPT
Outlier-Robust Spatial Perception: Hardness, General-Purpose Algorithms, and Guarantees
https://github.com/MIT-SPARK/STRIDE
https://github.com/MIT-SPARK/TEASER-plusplus
https://github.com/MKFMIKU/VIDM
Restormer: Efficient Transformer for High-Resolution Image Restoration
https://github.com/MLX15/TecoGAN
Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation
https://github.com/MQSchleich/SatelliteFAMOS
Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Image Stylization
https://github.com/MQSchleich/SatelliteGAN
Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Image Stylization
https://github.com/MRD-Git/Medical-Applications
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
https://github.com/MS-Mind/MS-Code-06/tree/main/Non_local
https://github.com/MS-Mind/MS-Code-06/tree/main/PAMTRI
https://github.com/MS-Mind/MS-Code-06/tree/main/PoseNet
Towards Better Generalization: Joint Depth-Pose Learning without PoseNet
https://github.com/MS-Mind/MS-Code-08/tree/main/Non_local
https://github.com/MS-P3/code4/tree/main/PPT
PPT: token-Pruned Pose Transformer for monocular and multi-view human pose estimation
https://github.com/MS-P3/code5/tree/main/graphormer
https://github.com/MSeeker1340/Vision2018-Pose
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/MVIG-SJTU/RMPE
Multi-Person Pose Estimation with Local Joint-to-Person Associations
https://github.com/Makunda/DeepLearningASL
https://github.com/Maluuba/GeNeVA
Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction
https://github.com/Maluuba/GeNeVA_datasets
Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction
https://github.com/Manan1811/Neural-Style-Transfer
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.