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Image Stylization

Image stylization is a task that involves transforming an input image into a new image that has a different style, while preserving the content of the original image. The goal of image stylization is to create visually appealing images with a specific style or aesthetic, such as impressionism, cubism, or surrealism. It can also be used to make images more visually appealing for specific applications, such as social media or advertising.

Papers

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Showing 1–25 of 64 papers

TitleStatusHype
OmniConsistency: Learning Style-Agnostic Consistency from Paired Stylization DataCode3
ToonifyGB: StyleGAN-based Gaussian Blendshapes for 3D Stylized Head Avatars—0
Balanced Image Stylization with Style Matching Score—0
Multiscale style transfer based on a Laplacian pyramid for traditional Chinese paintingCode0
Aesthetic Matters in Music Perception for Image Stylization: A Emotion-driven Music-to-Visual Manipulation—0
Content-style disentangled representation for controllable artistic image stylization and generation—0
Structure-Aware Stylized Image Synthesis for Robust Medical Image SegmentationCode0
The Role of Text-to-Image Models in Advanced Style Transfer Applications: A Case Study with DALL-E 3—0
AI-Driven Stylization of 3D Environments—0
WaSt-3D: Wasserstein-2 Distance for Scene-to-Scene Stylization on 3D Gaussians—0
MagicStyle: Portrait Stylization Based on Reference Image—0
Learning A Low-Level Vision Generalist via Visual Task PromptCode1
DiffArtist: Towards Structure and Appearance Controllable Image StylizationCode2
Ada-adapter:Fast Few-shot Style Personlization of Diffusion Model with Pre-trained Image Encoder—0
SRAGAN: Saliency Regularized and Attended Generative Adversarial Network for Chinese Ink-wash Painting Generation—0
Implicit Style-Content Separation using B-LoRACode3
One-Shot Structure-Aware Stylized Image SynthesisCode1
Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized StylizationCode3
Controlling Geometric Abstraction and Texture for Artistic ImagesCode1
Realization RGBD Image Stylization—0
Instant Photorealistic Neural Radiance Fields StylizationCode0
ReDi: Efficient Learning-Free Diffusion Inference via Trajectory RetrievalCode1
A Large-scale Film Style Dataset for Learning Multi-frequency Driven Film EnhancementCode1
Interactive Control over Temporal Consistency while Stylizing Video StreamsCode1
StyleTRF: Stylizing Tensorial Radiance Fields—0
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