Texture replacement in real images
Texture replacement in real images has many applications, such as interior design, digital movie making and computer graphics. The goal is to replace some specified texture patterns in an image while preserving lighting effects, shadows and occlusions. To achieve convincing replacement results we have to detect texture patterns and estimate the lighting map from a given image. Near regular planar texture patterns are considered in this paper. Given a sample texture patch, a standard tile is computed. Candidate texture regions are determined by mutual information between the standard tile and each image patch. Regions with high mutual information scores are used to estimate the admissible lighting distributions, which is represented by cached statistics. Spatial lighting change constraints are represented by a Markov random field model. Maximum a posteriori estimation of the texture segmentation and lighting map is solved in a stochastic annealing fashion, namely, the Markov chain Monte Carlo method. Visually satisfactory result is achieved using this statistical sampling model.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Realistic Dynamic Facial Textures From a Single Image Using GANs
We present a novel method to realistically puppeteer and animate a face from a single RGB image using a source video sequence. We begin by fitting a multilinear PCA model to obtain the 3D geometry and a single texture of…
3D geometryControllable Person Image Synthesis with Spatially-Adaptive Warped Normalization
Controllable person image generation aims to produce realistic human images with desirable attributes such as a given pose, cloth textures, or hairstyles. However, the large spatial misalignment between source and target…
Image GenerationImage-to-Image TranslationPose TransferTranslationDAGSM: Disentangled Avatar Generation with GS-enhanced Mesh
Text-driven avatar generation has gained significant attention owing to its convenience. However, existing methods typically model the human body with all garments as a single 3D model, limiting its usability, such as cl…
DenoisingRegularity-Driven Facade Matching Between Aerial and Street Views
We present an approach for detecting and matching building facades between aerial view and street-view images. We exploit the regularity of urban scene facades as captured by their lattice structures and deduced from med…
Carton dataset synthesis method for domain shift based on foreground texture decoupling and replacement
One major impediment in rapidly deploying object detection models for industrial applications is the lack of large annotated datasets. We currently have presented the Sacked Carton Dataset(SCD) that contains carton image…
Image Generationobject-detectionObject Detection