Papers SVBRDF Estimation
“SVBRDF Estimation” 태그가 달린 논문 11편 · 필터 해제
Single-image Reflectance and Transmittance Estimation from Any Flatbed Scanner
Flatbed scanners have emerged as promising devices for high-resolution, single-image material capture. However, existing approaches assume very specific conditions, such as uniform diffuse illumination, which are only av…
BRDF estimationImage-to-Image TranslationIntrinsic Image DecompositionMaterial Classification+2MatFusion: A Generative Diffusion Model for SVBRDF Capture
We formulate SVBRDF estimation from photographs as a diffusion task. To model the distribution of spatially varying materials, we first train a novel unconditional SVBRDF diffusion backbone model on a large set of 312,16…
modelSVBRDF EstimationMatSynth: A Modern PBR Materials Dataset
We introduce MatSynth, a dataset of 4,000+ CC0 ultra-high resolution PBR materials. Materials are crucial components of virtual relightable assets, defining the interaction of light at the surface of geometries. Given th…
SVBRDF EstimationMatFuse: Controllable Material Generation with Diffusion Models
Creating high-quality materials in computer graphics is a challenging and time-consuming task, which requires great expertise. To simplify this process, we introduce MatFuse, a unified approach that harnesses the generat…
SVBRDF EstimationUMat: Uncertainty-Aware Single Image High Resolution Material Capture
We propose a learning-based method to recover normals, specularity, and roughness from a single diffuse image of a material, using microgeometry appearance as our primary cue. Previous methods that work on single images …
Active LearningImage-to-Image TranslationMaterial RecognitionSVBRDF EstimationDiffuse Map Guiding Unsupervised Generative Adversarial Network for SVBRDF Estimation
Reconstructing materials in the real world has always been a difficult problem in computer graphics. Accurately reconstructing the material in the real world is critical in the field of realistic rendering. Traditionally…
Generative Adversarial NetworkSVBRDF EstimationMulti-view Gradient Consistency for SVBRDF Estimation of Complex Scenes under Natural Illumination
This paper presents a process for estimating the spatially varying surface reflectance of complex scenes observed under natural illumination. In contrast to previous methods, our process is not limited to scenes viewed u…
DisentanglementImage ReconstructionSVBRDF EstimationSurfaceNet: Adversarial SVBRDF Estimation from a Single Image
In this paper we present SurfaceNet, an approach for estimating spatially-varying bidirectional reflectance distribution function (SVBRDF) material properties from a single image. We pose the problem as an image translat…
Generative Adversarial NetworkSVBRDF EstimationTranslationOne Ring to Rule Them All: a simple solution to multi-view 3D-Reconstruction of shapes with unknown BRDF via a small Recurrent ResNet
This paper proposes a simple method which solves an open problem of multi-view 3D-Reconstruction for objects with unknown and generic surface materials, imaged by a freely moving camera and a freely moving point light so…
3D ReconstructionAllMulti-View 3D ReconstructionNovel View Synthesis+2Deep SVBRDF Estimation on Real Materials
Recent work has demonstrated that deep learning approaches can successfully be used to recover accurate estimates of the spatially-varying BRDF (SVBRDF) of a surface from as little as a single image. Closer inspection re…
SVBRDF EstimationSingle-Shot Neural Relighting and SVBRDF Estimation
We present a novel physically-motivated deep network for joint shape and material estimation, as well as relighting under novel illumination conditions, using a single image captured by a mobile phone camera. Our physica…
Inverse RenderingSVBRDF Estimation