Triangle Splatting
Name
xu-danielxu-meng-eecs-2025-thesis.pdf
Description
Thesis PDF
Size
136.66 MB
Format
Adobe PDF
Checksum (MD5)
9723a47a44aa0ea65e136b371b4d9dd4
Author(s)
Xu, Daniel
Advisor(s)
Sitzmann, Vincent
Date Issued
May 2025
Publisher
Massachusetts Institute of Technology
Abstract
We develop a differentiable rendering method for recovering 3D meshes of scenes from 2D images. Unlike existing approaches, our method does not rely on a differentiable renderers and is compatible with any standard mesh rasterizer. To our knowledge, it is the first mesh-based differentiable rendering method that is not reliant the use of visibility masks entirely. Beyond these conceptual advancements, we implemented a set of highly optimized kernels that enable efficient scene representation on a sparse voxel grid, effectively overcoming the cubic scaling bottleneck faced by similar methods. These innovations result in promising performance on unbounded real-world scenes with complex backgrounds.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
In Copyright - Educational Use Permitted
Copyright retained by author(s)
Persistent DSpace Link
