Concept decomposition for visual exploration and inspiration
A creative idea is often born from transforming, combining, and modifying ideas from existing
visual examples capturing various concepts. However, one cannot simply copy the concept …
visual examples capturing various concepts. However, one cannot simply copy the concept …
Grains: Generative recursive autoencoders for indoor scenes
We present a generative neural network that enables us to generate plausible 3D indoor
scenes in large quantities and varieties, easily and highly efficiently. Our key observation is …
scenes in large quantities and varieties, easily and highly efficiently. Our key observation is …
Joinable: Learning bottom-up assembly of parametric cad joints
Physical products are often complex assemblies combining a multitude of 3D parts modeled
in computer-aided design (CAD) software. CAD designers build up these assemblies by …
in computer-aided design (CAD) software. CAD designers build up these assemblies by …
Example-based synthesis of 3D object arrangements
We present a method for synthesizing 3D object arrangements from examples. Given a few
user-provided examples, our system can synthesize a diverse set of plausible new scenes …
user-provided examples, our system can synthesize a diverse set of plausible new scenes …
Dream lens: Exploration and visualization of large-scale generative design datasets
This paper presents Dream Lens, an interactive visual analysis tool for exploring and
visualizing large-scale generative design datasets. Unlike traditional computer aided …
visualizing large-scale generative design datasets. Unlike traditional computer aided …
3-sweep: Extracting editable objects from a single photo
We introduce an interactive technique for manipulating simple 3D shapes based on
extracting them from a single photograph. Such extraction requires understanding of the …
extracting them from a single photograph. Such extraction requires understanding of the …
Voxsegnet: Volumetric cnns for semantic part segmentation of 3d shapes
Volumetric representation has been widely used for 3D deep learning in shape analysis due
to its generalization ability and regular data format. However, for fine-grained tasks like part …
to its generalization ability and regular data format. However, for fine-grained tasks like part …
Sketch2Scene: Sketch-based co-retrieval and co-placement of 3D models
This work presents Sketch2Scene, a framework that automatically turns a freehand sketch
drawing inferring multiple scene objects to semantically valid, well arranged scenes of 3D …
drawing inferring multiple scene objects to semantically valid, well arranged scenes of 3D …
Learning part-based templates from large collections of 3D shapes
As large repositories of 3D shape collections continue to grow, understanding the data,
especially encoding the inter-model similarity and their variations, is of central importance …
especially encoding the inter-model similarity and their variations, is of central importance …
Im2struct: Recovering 3d shape structure from a single rgb image
We propose to recover 3D shape structures from single RGB images, where structure refers
to shape parts represented by cuboids and part relations encompassing connectivity and …
to shape parts represented by cuboids and part relations encompassing connectivity and …