3D Computer Vision; PointCloud Processing; 3D Reverse Engineering
Abstract :
[en] 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 processes and relating them to real objects. In this context, 3D reverse engineering of CAD models from 3D scans is considered to be one of the most sought-after goals for the CAD industry. However, recent efforts assume multiple simplifications limiting the applications in real-world settings. The SHARP Challenge 2023 aims at pushing the research a step closer to the real-world scenario of CAD reverse engineering from 3D scans through dedicated datasets and tracks. In this paper, we define the proposed SHARP 2023 tracks, describe the provided datasets, and propose a set of baseline methods along with suitable evaluation metrics to assess the performance of the track solutions. All proposed datasets along with useful routines and the evaluation metrics are publicly available.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT)
Disciplines :
Computer science
Author, co-author :
MALLIS, Dimitrios ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
ALI, Sk Aziz ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
DUPONT, Elona ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SnT) > CVI2
Cherenkova, Kseniya; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SnT) > CVI2 ; Artec 3D
KARADENIZ, Ahmet Serdar ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
KHAN, Mohammad Sadil ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
KACEM, Anis ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
Gleb, Gusev; Artec 3D
AOUADA, Djamila ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2
External co-authors :
no
Language :
English
Title :
SHARP Challenge 2023: Solving CAD History and pArameters Recovery from Point clouds and 3D scans. Overview, Datasets, Metrics, and Baselines.
Publication date :
03 October 2023
Event name :
International Conference on Computer Vision Workshops
Event place :
Paris, France
Event date :
from 02-10-2023 to 06-10-2023
Audience :
International
Journal title :
International Conference on Computer Vision Workshops
Peer reviewed :
Peer reviewed
Focus Area :
Security, Reliability and Trust
FnR Project :
FNR16849599 > Djamila Aouada > FREE-3D > Feature-based Reverse Engineering Of 3d Scans > 01/01/2022 > 31/12/2024 > 2021
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