Search Results for author:
Found 8 papers, 3 papers with code
DiffCSG: Differentiable CSG via Rasterization
Our algorithm builds upon CSG rasterization, which displays the result of boolean operations between primitives without explicitly computing the resulting mesh and, as such, bypasses black-box mesh processing.
CADTalk: An Algorithm and Benchmark for Semantic Commenting of CAD Programs
CAD programs are a popular way to compactly encode shapes as a sequence of operations that are easy to parametrically modify.
Deep scene-scale material estimation from multi-view indoor captures
The movie and video game industries have adopted photogrammetry as a way to create digital 3D assets from multiple photographs of a real-world scene.
Guided Fine-Tuning for Large-Scale Material Transfer
Our solution is extremely simple: we fine-tune a deep appearance-capture network on the provided exemplars, such that it learns to extract similar SVBRDF values from the target image.
Flexible SVBRDF Capture with a Multi-Image Deep Network
Empowered by deep learning, recent methods for material capture can estimate a spatially-varying reflectance from a single photograph.
Graphics I.3
Single-Image SVBRDF Capture with a Rendering-Aware Deep Network
Texture, highlights, and shading are some of many visual cues that allow humans to perceive material appearance in single pictures.
Graphics I.3
3D Sketching using Multi-View Deep Volumetric Prediction
The main strengths of our approach are its robustness to freehand bitmap drawings, its ability to adapt to different object categories, and the continuum it offers between single-view and multi-view sketch-based modeling.
Line Drawing Interpretation in a Multi-View Context
Many design tasks involve the creation of new objects in the context of an existing scene.
