Seminar for 3D Machine Learning - Winter 2024, Technical University of Munich
Instructor
This seminar will discuss recent developments in modern machine learning towards capturing geometric and semantic understanding of the 3D environments around us. Topics will include deep learning approaches for both generative and discriminative 3D tasks on various 3D representations such as point clouds, voxels, meshes.
Practical Course: Deep Learning for 3D Perception - Winter 2024, Technical University of Munich
Instructor
Takes an academic research focus on cutting-edge topics in computer vision, graphics, and machine learning. Topics cover 3D reconstruction, 3D semantic scene understanding, generative 3D modeling, dynamic modeling, self-supervised, weakly-supervised, and few-shot learning for 3D reconstruction and semantics.
Machine Learning for 3D Geometry - Winter 2024, Technical University of Munich
Instructor
Explore state-of-the-art algorithms for both supervised and unsupervised machine learning on 3D data, for both analysis and synthesis of 3D shapes and scenes.
Seminar for 3D Machine Learning - Summer 2024, Technical University of Munich
Instructor
This seminar will discuss recent developments in modern machine learning towards capturing geometric and semantic understanding of the 3D environments around us. Topics will include deep learning approaches for both generative and discriminative 3D tasks on various 3D representations such as point clouds, voxels, meshes.
Practical Course: Deep Learning for 3D Perception - Summer 2024, Technical University of Munich
Instructor
Takes an academic research focus on cutting-edge topics in computer vision, graphics, and machine learning. Topics cover 3D reconstruction, 3D semantic scene understanding, generative 3D modeling, dynamic modeling, self-supervised, weakly-supervised, and few-shot learning for 3D reconstruction and semantics.
Machine Learning for 3D Geometry - Summer 2024, Technical University of Munich
Instructor
Explore state-of-the-art algorithms for both supervised and unsupervised machine learning on 3D data, for both analysis and synthesis of 3D shapes and scenes.
Seminar for 3D Machine Learning - Winter 2023, Technical University of Munich
Instructor
This seminar will discuss recent developments in modern machine learning towards capturing geometric and semantic understanding of the 3D environments around us. Topics will include deep learning approaches for both generative and discriminative 3D tasks on various 3D representations such as point clouds, voxels, meshes.
Practical Course: Deep Learning for 3D Perception - Winter 2023, Technical University of Munich
Instructor
Takes an academic research focus on cutting-edge topics in computer vision, graphics, and machine learning. Topics cover 3D reconstruction, 3D semantic scene understanding, generative 3D modeling, dynamic modeling, self-supervised, weakly-supervised, and few-shot learning for 3D reconstruction and semantics.
Machine Learning for 3D Geometry - Winter 2023, Technical University of Munich
Instructor
Explore state-of-the-art algorithms for both supervised and unsupervised machine learning on 3D data, for both analysis and synthesis of 3D shapes and scenes.
Seminar for 3D Machine Learning - Summer 2023, Technical University of Munich
Instructor
This seminar will discuss recent developments in modern machine learning towards capturing geometric and semantic understanding of the 3D environments around us. Topics will include deep learning approaches for both generative and discriminative 3D tasks on various 3D representations such as point clouds, voxels, meshes.
Practical Course: Deep Learning for 3D Perception - Summer 2023, Technical University of Munich
Instructor
Takes an academic research focus on cutting-edge topics in computer vision, graphics, and machine learning. Topics cover 3D reconstruction, 3D semantic scene understanding, generative 3D modeling, dynamic modeling, self-supervised, weakly-supervised, and few-shot learning for 3D reconstruction and semantics.
Machine Learning for 3D Geometry - Summer 2023, Technical University of Munich
Instructor
Explore state-of-the-art algorithms for both supervised and unsupervised machine learning on 3D data, for both analysis and synthesis of 3D shapes and scenes.
Instructor
This lecture focuses on modern machine learning techniques, such as convolutional neural networks, recurrent neural networks, and generative techniques.
Seminar for 3D Machine Learning - Winter 2022, Technical University of Munich
Instructor
This seminar will discuss recent developments in modern machine learning towards capturing geometric and semantic understanding of the 3D environments around us. Topics will include deep learning approaches for both generative and discriminative 3D tasks on various 3D representations such as point clouds, voxels, meshes.
Practical Course: Deep Learning for 3D Perception - Winter 2022, Technical University of Munich
Instructor
Takes an academic research focus on cutting-edge topics in computer vision, graphics, and machine learning. Topics cover 3D reconstruction, 3D semantic scene understanding, generative 3D modeling, dynamic modeling, self-supervised, weakly-supervised, and few-shot learning for 3D reconstruction and semantics.
Machine Learning for 3D Geometry - Winter 2022, Technical University of Munich
Instructor
Explore state-of-the-art algorithms for both supervised and unsupervised machine learning on 3D data, for both analysis and synthesis of 3D shapes and scenes.
Seminar for 3D Machine Learning - Summer 2022, Technical University of Munich
Instructor
This seminar will discuss recent developments in modern machine learning towards capturing geometric and semantic understanding of the 3D environments around us. Topics will include deep learning approaches for both generative and discriminative 3D tasks on various 3D representations such as point clouds, voxels, meshes.
Practical Course: Deep Learning for 3D Perception - Summer 2022, Technical University of Munich
Instructor
Takes an academic research focus on cutting-edge topics in computer vision, graphics, and machine learning. Topics cover 3D reconstruction, 3D semantic scene understanding, generative 3D modeling, dynamic modeling, self-supervised, weakly-supervised, and few-shot learning for 3D reconstruction and semantics.
Machine Learning for 3D Geometry - Summer 2022, Technical University of Munich
Instructor
Explore state-of-the-art algorithms for both supervised and unsupervised machine learning on 3D data, for both analysis and synthesis of 3D shapes and scenes.
Geometric Modeling and Visualization - Summer 2022, Technical University of Munich
Instructor
Introduction to the fundamentals of computer graphics, with focus on techniques frequently used in engineering applications. Covers 1) Geometric Modeling, including polygonal surface representations, surface reconstruction, operations on surfaces, and subdivision surfaces. 2) Rendering, including an introduction to the GPU based graphics pipeline as well as basic techniques for image synthesis like lighting, shading, texture mapping, and transformations. 3) Scientific Visualization, including techniques for visualizing volumetric scalar fields and flow fields.
Seminar for 3D Machine Learning - Winter 2021, Technical University of Munich
Instructor
This seminar will discuss recent developments in modern machine learning towards capturing geometric and semantic understanding of the 3D environments around us. Topics will include deep learning approaches for both generative and discriminative 3D tasks on various 3D representations such as point clouds, voxels, meshes.
Machine Learning for 3D Geometry - Winter 2021, Technical University of Munich
Instructor
Explore state-of-the-art algorithms for both supervised and unsupervised machine learning on 3D data, for both analysis and synthesis of 3D shapes and scenes.
3D Scanning & Motion Capture - Winter 2021, Technical University of Munich
Instructor
Focus on cutting-edge 3D reconstruction approaches, including volumetric fusion on implicit functions, structure from motion, face tracking, and more.
Seminar for 3D Machine Learning - Summer 2021, Technical University of Munich
Instructor
This seminar will discuss recent developments in modern machine learning towards capturing geometric and semantic understanding of the 3D environments around us. Topics will include deep learning approaches for both generative and discriminative 3D tasks on various 3D representations such as point clouds, voxels, meshes.
Machine Learning for 3D Geometry - Summer 2021, Technical University of Munich
Instructor
Explore state-of-the-art algorithms for both supervised and unsupervised machine learning on 3D data, for both analysis and synthesis of 3D shapes and scenes.
3D Scanning & Motion Capture - Summer 2021, Technical University of Munich
Instructor
Focus on cutting-edge 3D reconstruction approaches, including volumetric fusion on implicit functions, structure from motion, face tracking, and more.
3D Scanning & Motion Capture - Winter 2020, Technical University of Munich
Co-Instructor
Focus on cutting-edge 3D reconstruction approaches, including volumetric fusion on implicit functions, structure from motion, face tracking, and more.
3D Scanning & Motion Capture - Summer 2020, Technical University of Munich
Co-Instructor
Focus on cutting-edge 3D reconstruction approaches, including volumetric fusion on implicit functions, structure from motion, face tracking, and more.
Co-Instructor
This lecture focuses on modern machine learning techniques, such as convolutional neural networks, recurrent neural networks, and generative techniques.
3D Scanning & Motion Capture - Winter 2019, Technical University of Munich
Co-Instructor
Focus on cutting-edge 3D reconstruction approaches, including volumetric fusion on implicit functions, structure from motion, face tracking, and more.
3D Scanning & Motion Capture - Summer 2019, Technical University of Munich
Co-Instructor
Focus on cutting-edge 3D reconstruction approaches, including volumetric fusion on implicit functions, structure from motion, face tracking, and more.
3D Scanning & Motion Capture - Winter 2018, Technical University of Munich
Co-Instructor
Focus on cutting-edge 3D reconstruction approaches, including volumetric fusion on implicit functions, structure from motion, face tracking, and more.
Introduction to Computer Graphics and Imaging (CS148) - Summer 2015, Stanford University
Teaching Assistant
Introduction to Computer Graphics and Imaging (CS148) - Summer 2014, Stanford University
Teaching Assistant