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Appearance Transfer
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Transfer of the appearance from one object to another.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Semantix: An Energy Guided Sampler for Semantic Style Transfer
Visual Persona: Foundation Model for Full-Body Human Customization
ReStyle3D: Scene-Level Appearance Transfer with Semantic Correspondences
LineArt: A Knowledge-guided Training-free High-quality Appearance Transfer for Design Drawing with Diffusion Model
Pose-Based Sign Language Appearance Transfer
Mask-guided cross-image attention for zero-shot in-silico histopathologic image generation with a diffusion model
Eye-for-an-eye: Appearance Transfer with Semantic Correspondence in Diffusion Models
Ctrl-X: Controlling Structure and Appearance for Text-To-Image Generation Without Guidance
FilterPrompt: A Simple yet Efficient Approach to Guide Image Appearance Transfer in Diffusion Models
ZeST: Zero-Shot Material Transfer from a Single Image
NeRF Analogies: Example-Based Visual Attribute Transfer for NeRFs
Unified Diffusion-Based Rigid and Non-Rigid Editing with Text and Image Guidance
Fine-grained Appearance Transfer with Diffusion Models
Disentangling Structure and Appearance in ViT Feature Space
Cross-Image Attention for Zero-Shot Appearance Transfer
Seeing is not Believing: An Identity Hider for Human Vision Privacy Protection
Splicing ViT Features for Semantic Appearance Transfer
Super-Resolution Appearance Transfer for 4D Human Performances
Few-Shot Human Motion Transfer by Personalized Geometry and Texture Modeling
Style and Pose Control for Image Synthesis of Humans from a Single Monocular View
Liquid Warping GAN with Attention: A Unified Framework for Human Image Synthesis
Two-Stream Appearance Transfer Network for Person Image Generation
Neural Crossbreed: Neural Based Image Metamorphosis
Pose-Guided High-Resolution Appearance Transfer via Progressive Training
Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis
Unsupervised Part-Based Disentangling of Object Shape and Appearance
Adversarial Training for Adverse Conditions: Robust Metric Localisation using Appearance Transfer
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.