Princeton CS597: Geometric Modeling and Analysis (Fall 2003)ĬreativeAI: Deep Learning for Graphics Datasets Princeton COS 526: Advanced Computer Graphics (Fall 2010) Stanford CS468: Machine Learning for 3D Data (Spring 2017) UCSD CSE291-I00: Machine Learning for 3D Data (Winter 2018) Stanford CS231A: Computer Vision-From 3D Reconstruction to Recognition (Winter 2018) Texture/Material Analysis and Synthesis.Parametric Morphable Model-based methods.⭐ ⭐ ⭐ ⭐ ⭐ ⭐ ⭐ ⭐ ⭐ ⭐ ⭐ ⭐ Table of Contents Together, I'm sure we can advance this field as a collaborative effort.
We have also created a Slack workplace for people around the globe to ask questions, share knowledge and facilitate collaborations. To contribute to this Repo, you may add content through pull requests or open an issue to let me know. To find related papers and their relationships, check out Connected Papers, which provides a neat way to visualize the academic field in a graph representation. I'll use the following icons to differentiate 3D representations: This repo is derived from my study notes and will be used as a place for triaging new research papers. In recent years, tremendous amount of progress is being made in the field of 3D Machine Learning, which is an interdisciplinary field that fuses computer vision, computer graphics and machine learning.
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