Papers with Code 아카이브
1 Image, 2*2 Stitching
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 0
- 보존된 평가 기록
- 0
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/vinod377/STN-OCR-Tensorflow
https://github.com/vinthony/s2crnet-demos
Spatial-Separated Curve Rendering Network for Efficient and High-Resolution Image Harmonization
https://github.com/vinx-2105/madgan-degan
https://github.com/vipermu/ganimation
GANimation: Anatomically-aware Facial Animation from a Single Image
https://github.com/vita-epfl/rock-pytorch
https://github.com/vlievin/Unet
https://github.com/vpsg-research/waveguard
GANimation: Anatomically-aware Facial Animation from a Single Image
https://github.com/vwegn/dm
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wallacemplira/ganhopper
GANHopper: Multi-Hop GAN for Unsupervised Image-to-Image Translation
https://github.com/wangyu33/rStarGAN-master
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
https://github.com/wangyuan249/Mymmt767
https://github.com/wasilone11/ICPR-RIP-2024
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/waterdisappear/nudt4mstar
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/weipeng0703/Pix2Pix_MindSpore_For_PaperWithCode/tree/main/Pix2Pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/wen227/Pokemon_Classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wentao99/pix2pixHD
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/wenxinxu/resnet-in-tensorflow
https://github.com/wenxinxu/resnet_in_tensorflow
https://github.com/wfwf10/feature-based-federated-transfer-learning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wileyw/DeepLearningDemos
Generative Adversarial Networks in Computer Vision: A Survey and Taxonomy
https://github.com/willylulu/RelGAN
RelGAN: Multi-Domain Image-to-Image Translation via Relative Attributes
https://github.com/winfried-loetzsch/deep-hist
DeepHist: Differentiable Joint and Color Histogram Layers for Image-to-Image Translation
https://github.com/winfried-loetzsch/wise
https://github.com/winycg/MCL-OKD
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wjy5446/pytorch-everybody-dance-now
https://github.com/wkcn/UGATIT-mxnet
https://github.com/wkhademi/ImageEnhancement
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/wkostuch/wild-style
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wljungbergh/neuroncap
https://github.com/wonbeomjang/cyclegan-pytorch
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/wondonghyeon/protest-detection-violence-estimation
https://github.com/woongjoonchoi/DeepLearningPaper-Reproducing/tree/master/Vgg
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wuqiyao20160118/mini_project-for-CIFAR10
https://github.com/wwwAych/AutoVideoColor
https://github.com/wxb589/Person_reID_baseline_pytorch-master
Joint Discriminative and Generative Learning for Person Re-identification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.