GALLERY: A DATASET AND ENVIRON-MENT FOR PROGRAMMATIC CAD RECONSTRUCTION Anonymous

Abstract

Parametric computer-aided design (CAD) is a standard paradigm used for the design of manufactured objects. CAD designers perform modeling operations, such as sketch and extrude, to form a construction sequence that makes up a final design. Despite the pervasiveness of parametric CAD and growing interest from the research community, a dataset of human designed 3D CAD construction sequences has not been available to-date. In this paper we present the Fusion 360 Gallery reconstruction dataset and environment for learning CAD reconstruction. We provide a dataset of 8,625 designs, comprising sequential sketch and extrude modeling operations, together with a complementary environment called the Fusion 360 Gym, to assist with performing CAD reconstruction. We outline a standard CAD reconstruction task, together with evaluation metrics, and present results from a novel method using neurally guided search to recover a construction sequence from a target geometry.

1. INTRODUCTION

The manufactured objects that surround us in everyday life are created in computer-aided design (CAD) software using common modeling operations such as sketch and extrude. With just these two modeling operations, a highly expressive range of 3D designs can be created (Figure 1 ). Parametric CAD files contain construction sequence information that is critical for documenting design intent, maintaining editablity, and downstream simulation and manufacturing. Despite the value of this information, it is often lost due to data translation or error and must be reverse engineered from geometry or even raw 3D scan data. The task of reconstructing CAD operations from geometry has been pursued for over 40 years (Shah et al., 2001) and is available in commercial CAD software using heuristic approaches (Autodesk, 2012; Dassault, 2019) . Recent advances in neural networks for 3D shape generation has spurred new interest in CAD reconstruction, due to the potential to generalize better and further automate this challenging problem. However, learning-based approaches 



Figure 1: Top: A subset of designs containing 3D CAD construction sequences from the Fusion 360 Gallery reconstruction dataset. Bottom: An example construction sequence using sketch and extrude modeling operations.

