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/rickyHong/py-faster-rcnn-repl-cudnn5-support
https://github.com/rickyhan/SimGAN-Captcha
Learning from Simulated and Unsupervised Images through Adversarial Training
https://github.com/rightlit/StackGAN-v2-rev
https://github.com/rightlit/cycle-image-gan-rev
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/rijuldhir/TSM
https://github.com/rikichou/mmpose
https://github.com/rishabh-vij/Neural_Style_transfer
https://github.com/rishavbb/Image_Captioning
https://github.com/rishidarkdevil/daam-i2i
What the DAAM: Interpreting Stable Diffusion Using Cross Attention
https://github.com/rishikksh20/Zero-Shot-TTS
Zero-Shot Text-to-Speech for Text-Based Insertion in Audio Narration
https://github.com/rishikksh20/iSTFTNet-pytorch
https://github.com/ritesh2212/DeepPhotoStyle_pytorch-master
https://github.com/riven314/PerceptualLoss-FastAI
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/riyakothari/NeuralStyleTransfer
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/rj-IIITH18/style_transfer_in_text
https://github.com/rkem1542/EDSR-pytorch
https://github.com/rnwzd/FSPBT-Image-Translation
Interactive Video Stylization Using Few-Shot Patch-Based Training
https://github.com/robotvisionmu/densemonoslam
https://github.com/roboverseorg/roboverse
https://github.com/rockstar-0000/lip_sync_test
A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wild
https://github.com/rogerwwww/PCA-GM
SuperGlue: Learning Feature Matching with Graph Neural Networks
https://github.com/rohitrango/Adversarial-Pose-Estimation
Adversarial PoseNet: A Structure-aware Convolutional Network for Human Pose Estimation
https://github.com/roimehrez/photorealism
Photorealistic Style Transfer with Screened Poisson Equation
https://github.com/romanus/code_tekinetal_iccv17
Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose Estimation
https://github.com/rongjiehuang/transpeech
GenerSpeech: Towards Style Transfer for Generalizable Out-Of-Domain Text-to-Speech
https://github.com/ronny3050/AdvFaces
https://github.com/rootAkash/vision.ai
https://github.com/rowantseng/FUnIE-GAN-PyTorch
Fast Underwater Image Enhancement for Improved Visual Perception
https://github.com/roxanasoto/AttGanESRGAN
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/royira/linguistic-binding-in-diffusion-models
https://github.com/rozumden/ShapeFromBlur
https://github.com/rozumden/tbd
https://github.com/rozumden/tbd3d
https://github.com/rpryzant/delete_retrieve_generate
Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer
https://github.com/rrmina/fast-neural-style-pytorch
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.