Artistic style transfer for videos
원문 초록
In the past, manually re-drawing an image in a certain artistic style required a professional artist and a long time. Doing this for a video sequence single-handed was beyond imagination. Nowadays computers provide new possibilities. We present an approach that transfers the style from one image (for example, a painting) to a whole video sequence. We make use of recent advances in style transfer in still images and propose new initializations and loss functions applicable to videos. This allows us to generate consistent and stable stylized video sequences, even in cases with large motion and strong occlusion. We show that the proposed method clearly outperforms simpler baselines both qualitatively and quantitatively.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
SA-LUT: Spatial Adaptive 4D Look-Up Table for Photorealistic Style Transfer
Implicit Inversion turns CLIP into a Decoder
Pseudo Multi-Source Domain Generalization: Bridging the Gap Between Single and Multi-Source Domain Generalization
CLIPGaussian: Universal and Multimodal Style Transfer Based on Gaussian Splatting
Graph Style Transfer for Counterfactual Explainability
Style Transfer with Diffusion Models for Synthetic-to-Real Domain Adaptation
토론
이 논문과 연결된 포럼 글이 아직 없습니다.