https://github.com/ninatu/mood_challenge
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer
Stroke-based Neural Painting and Stylization with Dynamically Predicted Painting Region
Texture Networks: Feed-forward Synthesis of Textures and Stylized Images
Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Image Stylization
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Customizing Sequence Generation with Multi-Task Dynamical Systems
Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?
Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artworks
Inverting face embeddings with convolutional neural networks
Domain Adaptation for Object Detection via Style Consistency
StyPath: Style-Transfer Data Augmentation For Robust Histology Image Classification
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Exploring the structure of a real-time, arbitrary neural artistic stylization network
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.