Papers Image Stylization
“Image Stylization” 태그가 달린 논문 64편 · 필터 해제
Instant Photorealistic Neural Radiance Fields Stylization
We present Instant Neural Radiance Fields Stylization, a novel approach for multi-view image stylization for the 3D scene. Our approach models a neural radiance field based on neural graphics primitives, which use a hash…
GPUImage GenerationImage StylizationPositionReDi: Efficient Learning-Free Diffusion Inference via Trajectory Retrieval
Diffusion models show promising generation capability for a variety of data. Despite their high generation quality, the inference for diffusion models is still time-consuming due to the numerous sampling iterations requi…
Image GenerationImage StylizationRetrievalA Large-scale Film Style Dataset for Learning Multi-frequency Driven Film Enhancement
Film, a classic image style, is culturally significant to the whole photographic industry since it marks the birth of photography. However, film photography is time-consuming and expensive, necessitating a more efficient…
Film SimulationImage EnhancementImage StylizationInteractive Control over Temporal Consistency while Stylizing Video Streams
Image stylization has seen significant advancement and widespread interest over the years, leading to the development of a multitude of techniques. Extending these stylization techniques, such as Neural Style Transfer (N…
Image StylizationOptical Flow EstimationStyle TransferVideo Stabilization+1StyleTRF: Stylizing Tensorial Radiance Fields
Stylized view generation of scenes captured casually using a camera has received much attention recently. The geometry and appearance of the scene are typically captured as neural point sets or neural radiance fields in …
Image StylizationNeRFEDICT: Exact Diffusion Inversion via Coupled Transformations
Finding an initial noise vector that produces an input image when fed into the diffusion process (known as inversion) is an important problem in denoising diffusion models (DDMs), with applications for real image editing…
DenoisingImage ReconstructionImage StylizationText-based Image Editing+1Touch and Go: Learning from Human-Collected Vision and Touch
The ability to associate touch with sight is essential for tasks that require physically interacting with objects in the world. We propose a dataset with paired visual and tactile data called Touch and Go, in which human…
Image StylizationLISA: Localized Image Stylization with Audio via Implicit Neural Representation
We present a novel framework, Localized Image Stylization with Audio (LISA) which performs audio-driven localized image stylization. Sound often provides information about the specific context of the scene and is closely…
Image StylizationObjectVisual LocalizationDiffStyler: Controllable Dual Diffusion for Text-Driven Image Stylization
Despite the impressive results of arbitrary image-guided style transfer methods, text-driven image stylization has recently been proposed for transferring a natural image into a stylized one according to textual descript…
DenoisingImage StylizationStyle TransferMultiStyleGAN: Multiple One-shot Image Stylizations using a Single GAN
Image stylization aims at applying a reference style to arbitrary input images. A common scenario is one-shot stylization, where only one example is available for each reference style. Recent approaches for one-shot styl…
Image StylizationOne-Shot Face StylizationWISE: Whitebox Image Stylization by Example-based Learning
Image-based artistic rendering can synthesize a variety of expressive styles using algorithmic image filtering. In contrast to deep learning-based methods, these heuristics-based filtering techniques can operate on high-…
Image StylizationImage-to-Image TranslationParameter PredictionStyle TransferPTGCF: Printing Texture Guided Color Fusion for Impressionism Oil Painting Style Rendering
As a major branch of Non-Photorealistic Rendering (NPR), image stylization mainly uses the computer algorithms to render a photo into an artistic painting. Recent work has shown that the extraction of style information s…
Image StylizationLearning Graph Neural Networks for Image Style Transfer
State-of-the-art parametric and non-parametric style transfer approaches are prone to either distorted local style patterns due to global statistics alignment, or unpleasing artifacts resulting from patch mismatching. In…
Image StylizationStyle TransferStylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learning
3D scene stylization aims at generating stylized images of the scene from arbitrary novel views following a given set of style examples, while ensuring consistency when rendered from different views. Directly applying me…
Image StylizationNeRFDomain Enhanced Arbitrary Image Style Transfer via Contrastive Learning
In this work, we tackle the challenging problem of arbitrary image style transfer using a novel style feature representation learning method. A suitable style representation, as a key component in image stylization tasks…
Contrastive LearningImage StylizationRepresentation LearningStyle TransferLearning Visual Styles from Audio-Visual Associations
From the patter of rain to the crunch of snow, the sounds we hear often convey the visual textures that appear within a scene. In this paper, we present a method for learning visual styles from unlabeled audio-visual dat…
Image StylizationImage Steganography based on Style Transfer
Image steganography is the art and science of using images as cover for covert communications. With the development of neural networks, traditional image steganography is more likely to be detected by deep learning-based…
Image SteganographyImage StylizationSteganalysisStyle TransferJoJoGAN: One Shot Face Stylization
A style mapper applies some fixed style to its input images (so, for example, taking faces to cartoons). This paper describes a simple procedure -- JoJoGAN -- to learn a style mapper from a single example of the style. J…
Image StylizationOne-Shot Face StylizationDigging Into Self-Supervised Learning of Feature Descriptors
Fully-supervised CNN-based approaches for learning local image descriptors have shown remarkable results in a wide range of geometric tasks. However, most of them require per-pixel ground-truth keypoint correspondence da…
Image-Based LocalizationImage RetrievalImage StylizationRetrieval+1UMFA: A photorealistic style transfer method based on U-Net and multi-layer feature aggregation
In this paper, we propose a photorealistic style transfer network to emphasize the natural effect of photorealistic image stylization. In general, distortion of the image content and lacking of details are two typical is…
DecoderImage ReconstructionImage StylizationStyle Transfer