[SGP-2022] Deep Learning on Point Clouds

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Point cloud is an important type of geometric data structure. They are simple and unified structures that avoid the combinatorial irregularities and complexities of meshes. These properties make point clouds widely used for 3D reconstruction or visual understanding applications, such as AR, autonomous driving, and robotics. This course will teach how we apply deep learning methods to point cloud data. We will cover the following topics in this short course and will end with some open problems.

• Basic neural architectures to process point cloud as input or to generate point cloud as output
• Scene-level understanding of static and dynamic point clouds
• Point cloud based inverse graphics
• Learning to convert point cloud to other 3D representations
• Learning to map point cloud with data in other modalities (images, languages)

SU Lab UC San Diego

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Thank you for this talk. The density of information is overwhelming and so I'll be coming back to this a few times!

chosencode

This is such a good resource on point cloud. Thank you for uploading

mkjav

Hello sir I am research scholar registered for phD.i am looking for stepwise latest algorithms and architecture for research in poin cloud. will you help please?

swatideshmukh

What camera do you recommend for taking photos and creating a 3D point cloud?

Micha-gvgv

Hello Su,
What does normal information means that the point cloud comes with?

vishwapriyagautam

[SGP-2022] Deep Learning on Point Clouds

[SGP-2022] Deep Learning on Point Clouds

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