4 citations · 13 across the 14 of their papers we have counts for
15 papers
NeuroSymbEAD: A Large Scale Neuro-Symbolic Caption Dataset for Omni-Directional Embodied Autonomous Driving
Muhammad Ahmed Ullah Khan, Mohammed Elamine, Sheikh Talha Uddin +3
This paper introduces NeuroSymbEAD, a large-scale neuro-symbolic caption dataset featuring an ego-centric knowledge graph (KG) of static and dynamic objects annotated with classes,…
A2Z-10M+: Geometric Deep Learning with A-to-Z BRep Annotations for AI-Assisted CAD Modeling and Reverse Engineering
Pritham Kumar Jena, Bhavika Baburaj, Tushar Anand +3
Reverse engineering and rapid prototyping of computer-aided design (CAD) models from 3D scans, sketches, or simple text prompts are vital in industrial product design. However, rec…
SCLARO: A Dataset for Grounded Scenario-Level Scene Understanding and ScenarioCLIP for Benchmarking
Advik Sinha, Saurabh Atreya, Aashutosh A +2
In the paradigm of computer vision-based precise real-world scene understanding, joint reasoning in terms of contextual understanding about the objects present in a scene, their in…
MARVEL-40M+: Multi-Level Visual Elaboration for High-Fidelity Text-to-3D Content Creation
Sankalp Sinha, Mohammad Sadil Khan, Muhammad Usama +4
Generating high-fidelity 3D content from text prompts remains a significant challenge in computer vision due to the limited size, diversity, and annotation depth of the existing da…
Text2CAD: Generating Sequential CAD Models from Beginner-to-Expert Level Text Prompts
Mohammad Sadil Khan, Sankalp Sinha, Talha Uddin Sheikh +3
Prototyping complex computer-aided design (CAD) models in modern softwares can be very time-consuming. This is due to the lack of intelligent systems that can quickly generate simp…
BRep Boundary and Junction Detection for CAD Reverse Engineering
Sk Aziz Ali, Mohammad Sadil Khan, Didier Stricker
In machining process, 3D reverse engineering of the mechanical system is an integral, highly important, and yet time consuming step to obtain parametric CAD models from 3D scans. T…
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…
HandVoxNet++: 3D Hand Shape and Pose Estimation using Voxel-Based Neural Networks
Jameel Malik, Soshi Shimada, Ahmed Elhayek +4
3D hand shape and pose estimation from a single depth map is a new and challenging computer vision problem with many applications. Existing methods addressing it directly regress h…
RPSRNet: End-to-End Trainable Rigid Point Set Registration Network using Barnes-Hut -Tree Representation
Sk Aziz Ali, Kerem Kahraman, Gerd Reis +1
We propose RPSRNet - a novel end-to-end trainable deep neural network for rigid point set registration. For this task, we use a novel -tree representation for the input point…
Fast Gravitational Approach for Rigid Point Set Registration with Ordinary Differential Equations
Sk Aziz Ali, Kerem Kahraman, Christian Theobalt +2
This article introduces a new physics-based method for rigid point set alignment called Fast Gravitational Approach (FGA). In FGA, the source and target point sets are interpreted…
HandVoxNet: Deep Voxel-Based Network for 3D Hand Shape and Pose Estimation from a Single Depth Map
Jameel Malik, Ibrahim Abdelaziz, Ahmed Elhayek +5
3D hand shape and pose estimation from a single depth map is a new and challenging computer vision problem with many applications. The state-of-the-art methods directly regress 3D…