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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/NateKoenig/https-github.com-Kautenja-a-neural-algorithm-of-artistic-style
https://github.com/NathanDeMaria/AugmentedCycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/Ne-ki-tos/Super_res
https://github.com/Neilblaze/Aerowave
https://github.com/Neroxn/Style-Aware-Normalized/tree/main/Project_Kargi
Style-Aware Normalized Loss for Improving Arbitrary Style Transfer
https://github.com/Net-Mist/style-transfer-tf2
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/NeuralVFX/lighting-swap-cyclegan
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/Neznakomec/ml-project-transformers
https://github.com/Nhat-Thanh/ESPCN-Pytorch
https://github.com/Nhat-Thanh/ESPCN-TF
https://github.com/Nhat-Thanh/SRCNN-Pytorch
https://github.com/Nhat-Thanh/SRCNN-TF
https://github.com/Nhat-Thanh/VDSR-Pytorch
Accurate Image Super-Resolution Using Very Deep Convolutional Networks
https://github.com/NicholasKX/ShowAndTell
https://github.com/NicicDamjan/SoftKompjuting
https://github.com/NieXC/pytorch-ppn
Generative Partition Networks for Multi-Person Pose Estimation
https://github.com/Nikhil619/Motion-direction-control-of-a-pi-robot-using-hand-movementss
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/NikhilBadami/YogiAI
Yoga-82: A New Dataset for Fine-grained Classification of Human Poses
https://github.com/Nirav-Agarwal/GANs
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/NiravRaiyani/Mask-R-CNN-for-water-detection
https://github.com/NitishaS-812k/Monet-CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/NiucunCode/Deep-Learning-proj2
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/NoMorningstar/style-transfer-1
https://github.com/NomiMalik0207/PedSynth-and-PedGNN-for-Pedestrian-Intention-Prediction
https://github.com/NonMagneticNeedle/vision.ai
https://github.com/OfekCohen1/Style-On-3D-Video
https://github.com/Oishani/Machine-Learning-Projects
https://github.com/Okery/PyTorch-Simple-MaskRCNN
https://github.com/Omkar-Ranadive/Domain-Adaptation-CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/One-sixth/pixelshuffle_invert_pytorch
https://github.com/Our4514/CAGFUZZ
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/Oussamayousre/Yoga_pose_recognizer
OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/PARC/intricate-art-neural-transfer
https://github.com/PDEUXA/AIF_CYCLEGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/PINTO0309/HeadPoseEstimation-WHENet-yolov4-onnx-openvino
WHENet: Real-time Fine-Grained Estimation for Wide Range Head Pose
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.