The ability to generate novel, diverse, and realistic 3D shapes along with associated part
semantics and structure is central to many applications requiring high-quality 3D assets or …

This report surveys advances in deep learning‐based modelling techniques that address
four different 3D indoor scene analysis tasks, as well as synthesis of 3D indoor scenes. We …

We introduce a learning framework for automated floorplan generation which combines
generative modeling using deep neural networks and user-in-the-loop designs to enable …

Abstract 3D models of objects and scenes are critical to many academic disciplines and
industrial applications. Of particular interest is the emerging opportunity for 3D graphics to …

Visual imitation learning has achieved impressive progress in learning unimanual
manipulation tasks from a small set of visual observations, thanks to the latest advances in …

Synthesizing realistic 3D indoor scenes is a challenging task that traditionally relies on
manual arrangement and annotation by expert designers. Recent advances in …

Next generation smart and augmented reality systems demand a computational
understanding of monocular footage that captures humans in physical spaces to reveal …

We present a novel workflow based on artificial intelligence (AI) techniques to automate
interior design processes. We discuss the essential steps for creating an intelligent agent …

A central goal of computer graphics is to provide tools for designing and simulating real or
imagined artifacts. An understanding of functionality is important in enabling such modeling …

In this paper, we present a system that automatically populates indoor virtual scenes with
furniture objects and optimizes their positions and orientations with respect to aesthetic …