https://github.com/MuMiN-dataset/mumin-trawl
MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset
Papers with Code 아카이브
2D Classification
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MuhamedKamil/Neural-Style-Transfer-
https://github.com/Mukosame/Zooming-Slow-Mo-CVPR-2020
https://github.com/MuradBozik/audio-style-transfer
MelGAN-VC: Voice Conversion and Audio Style Transfer on arbitrarily long samples using Spectrograms
https://github.com/Muthu2093/U-Net-for-Brain-Tumor-Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/Myyyr/transseg2d
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/NANSHANB/StereoR-CNN
Stereo R-CNN based 3D Object Detection for Autonomous Driving
https://github.com/NASA-NeMO-Net/NeMO-Net
https://github.com/NBAiLab/notram
Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach
https://github.com/NBvinay/vinb-ghost-car
https://github.com/NCNU-OpenSource/What-are-you-
https://github.com/NDCHIRO/Cartoonizer
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/NERSC/sc21-dl-tutorial
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/NEUAutonomousDriving408/CIVCAutonomousDriving
https://github.com/NEUdeep/Swin-Transformer-Object-Detection
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/NU-LL/lighttrack-
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/NVIDIA/DeepLearningExamples
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/LanguageModeling/Transformer-XL
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context
https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow/LanguageModeling/Transformer-XL
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context
https://github.com/NVIDIA/MinkowskiEngine
Generative Sparse Detection Networks for 3D Single-shot Object Detection
https://github.com/NVIDIA/NeMo-Curator
https://github.com/NVIDIA/mellotron
https://github.com/NVIDIA/radtts
Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis
https://github.com/NVIDIA/retinanet-examples
https://github.com/NVIDIAAICITYCHALLENGE/AICity_Team6_ISU
R-FCN: Object Detection via Region-based Fully Convolutional Networks
https://github.com/NVlabs/DG-Net
https://github.com/NVlabs/On-Learning-Sets-of-Symmetric-Elements
https://github.com/NVlabs/PAMTRI
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/NVlabs/STL
https://github.com/NVlabs/industreallib
https://github.com/NYU-DICE-Lab/open_clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/NZ99/bottleneck-transformer-flax
https://github.com/NaCl-Ocean/Anchor_free_detection_rotation
1st Place Solutions of Waymo Open Dataset Challenge 2020 -- 2D Object Detection Track
https://github.com/Nacriema/Loss-Functions-For-Semantic-Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/NamSahng/SingingStyleTransfer
Singing Style Transfer Using Cycle-Consistent Boundary Equilibrium Generative Adversarial Networks
https://github.com/Nandu960/Road-Asset-Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.