CVPR 2025 - The 2nd Point Cloud Tutorial
All You Need To Know About 3D Point Cloud
June 11, 2025 at 202A
June 11, 2025 at 202A
Point cloud is a data structure that is quite prevalent in 3D vision, which plays an important role in eras like 3D perception, 3D generation, autonomous driving, embodied AI, etc. However, there has not been a comprehensive resource that covers the state-of-the-art approaches and engineering details in point cloud processing. This tutorial aims to provide a comprehensive understanding of point cloud processing and analysis. Participants will delve into various aspects of point cloud data, exploring fundamental layers, network engineering considerations and pre-training technology for point cloud processing. Through a combination of lectures, attendees will gain insights into the latest developments in the field and learn how to make informed choices when working with point cloud data. For the 2nd point cloud tutorial at CVPR 2025, we aim to move beyond traditional topics like backbone design and pre-training technologies covered in the 1st tutorial. This time, we will also explore challenges and opportunities in applications such as Autonomous Driving, Robotic Learning, and Egocentric Perception in AR/VR. With a diverse background spanning industry and academia, foundational research, and application-driven innovations, we offer a comprehensive perspective on the future of point cloud technology.
09: 00 - 09: 10
09: 10 - 10: 00
10: 00 - 10: 50
10: 50 - 11: 00
11: 00 - 11: 40
11: 40 - 12: 40
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Welcome & Introduction
Transformer Architecture for Point Clouds
Sparse Representations for Spatial Cognition (SSL)
Break
Deep Architectures for Point Clouds: the Initial Steps
Point Cloud from Videos
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  |- CUT3R
Xiaoyang Wu
Hengshuang Zhao
Xiaoyang Wu
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Leonidas Guibas
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Christian Rupprecht
Qianqian Wang
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14: 00 - 14: 10
14: 10 - 15: 00
15: 00 - 15: 50
15: 50 - 16: 00
16: 00 - 16: 50
16: 50 - 17: 40
Welcome & Introduction
Point Cloud for Spatial and Temporal Imaginations
Point Cloud for Robotic
Break
Point Cloud for Egocentric Perception (Project Aria)
Point Cloud for Autonomous Driving
Kaichun Mo
Fuxin Li
Kaichun Mo & Adithya Murali
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Julian Straub
Shenlong Wang
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