Generating 3D Point Clouds
6 papers with code • 0 benchmarks • 0 datasets
These leaderboards are used to track progress in Generating 3D Point Clouds
Deep generative architectures provide a way to model not only images but also complex, 3-dimensional objects, such as point clouds.
Constructing high-quality generative models for 3D shapes is a fundamental task in computer vision with diverse applications in geometry processing, engineering, and design.
Much of the success of deep learning is drawn from building architectures that properly respect underlying symmetry and structure in the data on which they operate - a set of considerations that have been united under the banner of geometric deep learning.
This is in stark contrast to state-of-the-art generative image models, which produce samples in a number of seconds or minutes.