Elsewhere

Courses

• Machine Learning for Inverse Graphics
  (MIT 6.S980, Prof. Vincent Sitzmann)
• Graduate Computer Vision
  (UC Berkeley 280, Prof.Alexei Efros)
• Learning for 3D Vision
  (CMU 16-889, Prof. Shubham Tulsiani)
• Advances in Computer Vision
  (MIT 6.819/6.869, Profs. Bill Freeman, Phillip Isola, Antonio Torralba)
• Deep Learning II, Part "Geometric Deep Learning"
  (University of Amsterdam 52042DEL6Y, Prof. Erik Bekkers)
• Computer Graphics in the Era of AI
  (Stanford CS348I, Profs. C. Karen Liu and Jiajun Wu)
• Computer Vision
  (University of Tübingen ML-4360, Prof. Andreas Geiger)
• Machine Learning Meets Geometry
  (UCSD CSE291, Prof. Hao Su)
• Machine Learning for 3D Data
  (U. Stanford cs468, Prof. Leo Guibas)
• Deep Learning for Computer Vision
  (U. Michigan EECS 490.008, Prof. Justin Johnson)
• Introduction to Deep Learning
  (MIT 6.S191, Prof. Alex Amini)
• Numerical Methods for Visual Computing and Machine Learning
  (EPFL CS-328, Prof. Wenzel Jakob)

Previous CG Courses at IMPA

• AI Graphics - Theory and Practice (2023)
• Machine Learning for Modeling and Rendering (2022)

NYU Courses - 2024 (Local Access)

• Machine Learning
• Deep Learning
• Special Topics: Advanced Machine Learning
• Special Topics: Geometric Modeling
• Special Topics: Vision Meets Machine Learning
• Special Topics: Mathematics of Deep Learning
• Special Topics in DS: Introduction to Computer Vision
• Special Topics: Conceptual Gaps in Modern Machine Learning
• Special Topics: Computer Graphics

Workshops & Seminars

• Deep Learning Geometric Shape Modeling and Reconstruction
  (CVPR 2020)
• Seminar on Geometry Processing and 3D Computer Vision
  (3DGV)

Tutorials

• A Tutorial on 3D Deep Learning
  (CVPR 2017)
• Deep Learning for Geometric Data
  (SGP 2020)
• Deep Learning on Meshes
  (SGP 2021)
• Neural Volumetric Rendering for Computer Vision
  (ECCV 2022)

Portals

• 3D Machine Learning

• Geometric Deep Learning

• Holistic 3D Reconstruction