Introduction In the rapidly evolving field of 3D computer vision and artificial intelligence, one of the most challenging tasks remains the ability to reconstruct editable, parametric 3D models from simple visual inputs. CADE Simu 3D (Computer-Aided Design & Engineering Simulated 3D) has emerged as a notable benchmark and dataset designed to train and evaluate models on exactly this problem. By bridging the gap between raw geometry and structured CAD (Computer-Aided Design) representations, CADE Simu 3D pushes the boundaries of how machines understand and recreate the designed world. What is CADE Simu 3D? CADE Simu 3D is a large-scale synthetic dataset composed of simulated 3D scenes that pair depth and RGB imagery with their underlying CAD construction sequences. Unlike traditional 3D datasets that provide only static meshes or point clouds, CADE Simu 3D focuses on the procedural nature of design. Each object in the dataset is generated from a parametric CAD kernel (e.g., extrusion, revolution, Boolean operations), and the data includes the full command history—the "recipe"—used to build the shape.
Introduction In the rapidly evolving field of 3D computer vision and artificial intelligence, one of the most challenging tasks remains the ability to reconstruct editable, parametric 3D models from simple visual inputs. CADE Simu 3D (Computer-Aided Design & Engineering Simulated 3D) has emerged as a notable benchmark and dataset designed to train and evaluate models on exactly this problem. By bridging the gap between raw geometry and structured CAD (Computer-Aided Design) representations, CADE Simu 3D pushes the boundaries of how machines understand and recreate the designed world. What is CADE Simu 3D? CADE Simu 3D is a large-scale synthetic dataset composed of simulated 3D scenes that pair depth and RGB imagery with their underlying CAD construction sequences. Unlike traditional 3D datasets that provide only static meshes or point clouds, CADE Simu 3D focuses on the procedural nature of design. Each object in the dataset is generated from a parametric CAD kernel (e.g., extrusion, revolution, Boolean operations), and the data includes the full command history—the "recipe"—used to build the shape.