1 citations · 2 across the 5 of their papers we have counts for
5 papers
CAD-SIGNet: CAD Language Inference from Point Clouds using Layer-wise Sketch Instance Guided Attention
Mohammad Sadil Khan, Elona Dupont, Sk Aziz Ali +3
Reverse engineering in the realm of Computer-Aided Design (CAD) has been a longstanding aspiration, though not yet entirely realized. Its primary aim is to uncover the CAD process…
SHARP Challenge 2023: Solving CAD History and pArameters Recovery from Point clouds and 3D scans. Overview, Datasets, Metrics, and Baselines
Dimitrios Mallis, Sk Aziz Ali, Elona Dupont +6
Recent breakthroughs in geometric Deep Learning (DL) and the availability of large Computer-Aided Design (CAD) datasets have advanced the research on learning CAD modeling processe…
DELO: Deep Evidential LiDAR Odometry using Partial Optimal Transport
Sk Aziz Ali, Djamila Aouada, Gerd Reis +1
Accurate, robust, and real-time LiDAR-based odometry (LO) is imperative for many applications like robot navigation, globally consistent 3D scene map reconstruction, or safe motion…
CADOps-Net: Jointly Learning CAD Operation Types and Steps from Boundary-Representations
Elona Dupont, Kseniya Cherenkova, Anis Kacem +4
3D reverse engineering is a long sought-after, yet not completely achieved goal in the Computer-Aided Design (CAD) industry. The objective is to recover the construction history of…
TSCom-Net: Coarse-to-Fine 3D Textured Shape Completion Network
Ahmet Serdar Karadeniz, Sk Aziz Ali, Anis Kacem +2
Reconstructing 3D human body shapes from 3D partial textured scans remains a fundamental task for many computer vision and graphics applications -- e.g., body animation, and virtua…