Proceedings of theWorkshop on 3D Geometry Generation for Scientific Computing

被引：0

作者：

de Chanlatte, Marissa Ramirez ^{[1
]}

Colella, Phil ^{[2
]}

Darrell, Trevor ^{[1
]}

Carlson, Alexandra Katherine ^{[3
]}

de With, Peter H. N. ^{[4
]}

Deng, Huayu ^{[5
]}

Guan, Shanyan ^{[5
]}

Hays, James ^{[6
]}

Houben, Tim ^{[4
]}

Huisman, Thomas ^{[7
]}

Jaipuria, Nikita ^{[8
]}

Johansen, Hans ^{[2
]}

Khalid, Shuja ^{[9
]}

Krishnan, Akshay ^{[6
]}

Li, Chuming ^{[10
]}

Pisarenco, Maxim ^{[7
]}

Raj, Amit ^{[11
]}

Rudzicz, Frank ^{[12
]}

Schoonbeek, Tim J. ^{[4
]}

Sridhar, Sandhya ^{[6
]}

Tseng, Nathan ^{[8
]}

van der Sommen, Fons ^{[4
]}

Wang, Chen ^{[13
]}

Wang, Yunbo ^{[5
]}

Wu, Tong ^{[14
]}

Yang, Xiaokang ^{[5
]}

Yao, Jiawei ^{[15
]}

Young, Derek ^{[16
]}

Zhang, Xianling ^{[17
]}

机构：

[1] Univ Calif Berkeley, Berkeley, CA 94720 USA

[2] Lawrence Berkeley Natl Lab, Berkeley, CA USA

[3] Univ Michigan, Ann Arbor, MI USA

[4] Eindhoven Univ Technol, Eindhoven, Netherlands

[5] Shanghai Jiao Tong Univ, Shanghai, Peoples R China

[6] Georgia Inst Technol, Atlanta, GA USA

[7] ASML, Veldhoven, Netherlands

[8] Ford Motor Co, Detroit, MI USA

[9] Univ Toronto, Toronto, ON, Canada

[10] Univ Sydney, Sydney, Australia

[11] Google, Mountain View, CA USA

[12] Dalhousie Univ, Halifax, NS, Canada

[13] Univ Penn, Philadelphia, PA 19104 USA

[14] Amazon, Seattle, WA USA

[15] Univ Washington, Seattle, WA 98195 USA

[16] Univ Calif Davis, Davis, CA USA

[17] Ford Greenfield Labs, Palo Alto, CA USA

来源：

2024 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION WORKSHOPS, WACVW 2024 | 2024年

关键词：

D O I：

10.1109/WACVW60836.2024.00088

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

High-fidelity 3D geometries of the natural and built world around us are an essential part of answering some of the most pressing scientific questions of our day. Through advances in deep learning, computer vision, and artificial intelligence more broadly, much progress has been made in reconstructing real geometries from images and/or sparse data, but these methods are just beginning to be applied to scientific problems. On January 7th, 2024 we bring together researchers from computer vision, applied mathematics, and several scientific disciplines, to discuss the state of the art in 3D geometry generation and how it can be applied to open problems in science. This paper summarizes a selection of the talks and papers that have been accepted.

引用

页码：762 / 766

页数：5

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