The SHApe Recovery from Partial textured 3D scans challenge, SHARP 2020, is the first edition of a challenge fostering and benchmarking methods for recovering complete textured 3D scans from raw incomplete data. SHARP 2020 is organized as a workshop in conjunction with ECCV 2020. There are two complementary challenges, the first one on 3D human scans, and the second one on generic objects. Challenge 1 is further split into two tracks, focusing, first, on large body and clothing regions, and, second, on fine body details. A novel evaluation metric is proposed to quantify jointly the shape reconstruction, the texture reconstruction, and the amount of completed data. Additionally, two unique datasets of 3D scans are proposed, to provide raw gr...
Performing 3D reconstruction from a single 2D input is a challenging problem that is trending in lit...
We have created a new benchmarking dataset for testing non-rigid 3D shape retrieval algorithms, one ...
New scanning technologies are increasing the importance of 3D mesh data and the need for algorithms ...
International audienceThe SHApe Recovery from Partial textured 3D scans challenge, SHARP 2020, is th...
Various practical applications in computer vision are related to the human body. These involve repre...
3D models of humans are commonly used within computer graphics and vision, and so the ability to dis...
We propose 3DBooSTeR, a novel method to recover a textured 3D body mesh from a textured partial 3D s...
International audienceWe address the problem of estimating human pose and body shape from 3D scans o...
We have created a new benchmarking dataset for testing non-rigid 3D shape retrieval algorithms, one ...
3D textured shape recovery from partial scans is crucial for many real-world applications. Existing ...
peer reviewedReconstructing 3D human body shapes from 3D partial textured scans remains a fundamenta...
© 2018 IEEE. We study 3D shape modeling from a single image and make contributions to it in three as...
We present a novel approach for obtaining a complete and consistent 3D model representation from inc...
International audienceStatistical models of 3D human shape and pose learned from scan databases have...
Statistical models of 3D human shape and pose learned from scan databases have developed into valuab...
Performing 3D reconstruction from a single 2D input is a challenging problem that is trending in lit...
We have created a new benchmarking dataset for testing non-rigid 3D shape retrieval algorithms, one ...
New scanning technologies are increasing the importance of 3D mesh data and the need for algorithms ...
International audienceThe SHApe Recovery from Partial textured 3D scans challenge, SHARP 2020, is th...
Various practical applications in computer vision are related to the human body. These involve repre...
3D models of humans are commonly used within computer graphics and vision, and so the ability to dis...
We propose 3DBooSTeR, a novel method to recover a textured 3D body mesh from a textured partial 3D s...
International audienceWe address the problem of estimating human pose and body shape from 3D scans o...
We have created a new benchmarking dataset for testing non-rigid 3D shape retrieval algorithms, one ...
3D textured shape recovery from partial scans is crucial for many real-world applications. Existing ...
peer reviewedReconstructing 3D human body shapes from 3D partial textured scans remains a fundamenta...
© 2018 IEEE. We study 3D shape modeling from a single image and make contributions to it in three as...
We present a novel approach for obtaining a complete and consistent 3D model representation from inc...
International audienceStatistical models of 3D human shape and pose learned from scan databases have...
Statistical models of 3D human shape and pose learned from scan databases have developed into valuab...
Performing 3D reconstruction from a single 2D input is a challenging problem that is trending in lit...
We have created a new benchmarking dataset for testing non-rigid 3D shape retrieval algorithms, one ...
New scanning technologies are increasing the importance of 3D mesh data and the need for algorithms ...