The Visual Computing & Artificial Intelligence Group offers a variety of lectures and seminars on a regular basis, covering hot areas in computer graphics, vision, and machine learning. Further details are provided on the corresponding lecture websites.

2023 Winter


DescriptionThis hands-on lecture focuses on cutting-edge 3D reconstruction approaches, including volumetric fusion approaches on implicit functions, face tracking, hand tracking, and much more! We also cover essential optimization techniques such as Gauss-Newton and Levenberg-Marquardt.
ContactProf. Dr. Matthias Nießner
TAs: M.Sc. Artem Sevastopolsky,  M.Sc. Lukas Höllein,  M.Sc. Marc Benedí San Millán
DescriptionThis practical offers a deep-dive into recent advances in 3D scanning and spatial machine learning. Projects span the whole semester and the objective can cover a variety of computer vision problems as large-scale 3D scanning, body tracking, face reconstruction and much more!
ContactM.Sc. Simon Giebenhain,   M.Sc. Tobias Kirschstein
DescriptionAdvanced Deep Learning. This lecture focuses on cutting edge Deep Learning techniques for computer vision with a heavy focus on Neural Rendering, Generative Adversarial Networks (GANs), Recurrent Neural Networks (RNNs), and many more topics related to the visual computing lab. Part of the lecture is a semester-long project with a deep dive on modern DL methods.
ContactProf. Dr. Matthias Nießner
TAs: M.Sc. Barbara Rössle,  M.Sc. David Rozenberszki,  M.Sc. Ziya Erkoç,  Dr. Lei Li
DescriptionThis practical offers a deep stint into recent advances in Deep Learning and AI. Over the course we will carefully look into recent research highlights and implement hands-on state-of-the-art algorithms through engaging group projects.
ContactProf. Dr. Matthias Nießner
DescriptionIntroduction to Deep Learning. This lecture focuses on modern machine learning techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Models (GANs).
ContactProf. Dr. Matthias Nießner
TAs: M.Sc. Yujin Chen,  M.Sc. Guy Gafni,  M.Sc. Manuel Dahnert
DescriptionThis is the research seminar of the Visual Computing Group. We discuss ongoing work in the direction of Neural Radiance Fields (NeRFs).
ContactM.Sc. Yawar Siddiqui,   M.Sc. Shenhan Qian
DescriptionThis colloquium invites prominent researchers to present new and exciting work across various fields in computer vision and artificial intelligence.
ContactM.Sc. Shivangi Aneja
DescriptionIn this course, the students will autonomously investigate recent research on fundamental concepts as well as recently developed 3D Computer Vision techniques. Independent investigation for further reading, critical analysis, and evaluation of the topic is required.
ContactM.Sc. Shivangi Aneja,   M.Sc. Peter Kocsis

2023 Summer


DescriptionThis hands-on lecture focuses on cutting-edge 3D reconstruction approaches, including volumetric fusion approaches on implicit functions, face tracking, hand tracking, and much more! We also cover essential optimization techniques such as Gauss-Newton and Levenberg-Marquardt.
ContactProf. Dr. Matthias Nießner
TAs: M.Sc. Artem Sevastopolsky,  M.Sc. Lukas Höllein,  M.Sc. Andrei Burov
DescriptionThis practical offers a deep-dive into recent advances in 3D scanning and spatial machine learning. Projects span the whole semester and the objective can cover a variety of computer vision problems as large-scale 3D scanning, body tracking, face reconstruction and much more!
ContactM.Sc. Simon Giebenhain,   M.Sc. Tobias Kirschstein
DescriptionAdvanced Deep Learning. This lecture focuses on cutting edge Deep Learning techniques for computer vision with a heavy focus on Neural Rendering, Generative Adversarial Networks (GANs), Recurrent Neural Networks (RNNs), and many more topics related to the visual computing lab. Part of the lecture is a semester-long project with a deep dive on modern DL methods.
ContactProf. Dr. Matthias Nießner
TAs: M.Sc. Dave Zhenyu Chen,  Dr. Yinyu Nie,  M.Sc. Barbara Rössle,  M.Sc. David Rozenberszki
DescriptionThis practical offers a deep stint into recent advances in Deep Learning and AI. Over the course we will carefully look into recent research highlights and implement hands-on state-of-the-art algorithms through engaging group projects.
ContactProf. Dr. Matthias Nießner
DescriptionIntroduction to Deep Learning. This lecture focuses on modern machine learning techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Models (GANs).
ContactProf. Dr. Matthias Nießner
TAs: M.Sc. Junwen Huang,  M.Sc. Yujin Chen,  M.Sc. Guy Gafni,  M.Sc. Manuel Dahnert
DescriptionThis is the research seminar of the Visual Computing Group. We discuss ongoing work in the direction of Neural Radiance Fields (NeRFs).
ContactM.Sc. Yawar Siddiqui,   M.Sc. Shenhan Qian
DescriptionThis colloquium invites prominent researchers to present new and exciting work across various fields in computer vision and artificial intelligence.
ContactM.Sc. Shivangi Aneja
DescriptionIn this course, the students will autonomously investigate recent research on fundamental concepts as well as recently developed 3D Computer Vision techniques. Independent investigation for further reading, critical analysis, and evaluation of the topic is required.
ContactM.Sc. Shivangi Aneja,   M.Sc. Peter Kocsis

2022 Winter


DescriptionThis hands-on lecture focuses on cutting-edge 3D reconstruction approaches, including volumetric fusion approaches on implicit functions, face tracking, hand tracking, and much more! We also cover essential optimization techniques such as Gauss-Newton and Levenberg-Marquardt.
ContactProf. Dr. Matthias Nießner
TAs: M.Sc. Artem Sevastopolsky,  M.Sc. Lukas Höllein,  M.Sc. Andrei Burov
DescriptionThis practical offers a deep-dive into recent advances in 3D scanning and spatial machine learning. Projects span the whole semester and the objective can cover a variety of computer vision problems as large-scale 3D scanning, body tracking, face reconstruction and much more!
ContactM.Sc. Jiapeng Tang,   M.Sc. Peter Kocsis
DescriptionAdvanced Deep Learning. This lecture focuses on cutting edge Deep Learning techniques for computer vision with a heavy focus on Neural Rendering, Generative Adversarial Networks (GANs), Recurrent Neural Networks (RNNs), and many more topics related to the visual computing lab. Part of the lecture is a semester-long project with a deep dive on modern DL methods.
ContactProf. Dr. Matthias Nießner
TAs: M.Sc. Dave Zhenyu Chen,  Dr. Yinyu Nie,  M.Sc. Barbara Rössle,  M.Sc. David Rozenberszki
DescriptionThis practical offers a deep stint into recent advances in Deep Learning and AI. Over the course we will carefully look into recent research highlights and implement hands-on state-of-the-art algorithms through engaging group projects.
ContactProf. Dr. Matthias Nießner
DescriptionIntroduction to Deep Learning. This lecture focuses on modern machine learning techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Models (GANs).
ContactProf. Dr. Angela Dai
TAs: M.Sc. Junwen Huang,  M.Sc. Yujin Chen,  M.Sc. Manuel Dahnert
DescriptionThis is the research seminar of the Visual Computing Group. We discuss ongoing work in the direction of Neural Radiance Fields (NeRFs).
ContactM.Sc. Guy Gafni,   M.Sc. Yawar Siddiqui
DescriptionThis colloquium invites prominent researchers to present new and exciting work across various fields in computer vision and artificial intelligence.
ContactM.Eng. Dejan Azinović
DescriptionThis is the research seminar of the Visual Computing Group. We discuss hot trends and ongoing work in computer vision, graphics, and machine learning.
ContactM.Sc. Norman Müller,   M.Sc. Shivangi Aneja

2022 Summer


DescriptionThis hands-on lecture focuses on cutting-edge 3D reconstruction approaches, including volumetric fusion approaches on implicit functions, face tracking, hand tracking, and much more! We also cover essential optimization techniques such as Gauss-Newton and Levenberg-Marquardt.
ContactProf. Dr. Matthias Nießner
TAs: M.Sc. Artem Sevastopolsky,  M.Sc. Lukas Höllein,  M.Sc. Andrei Burov
DescriptionThis practical offers a deep-dive into recent advances in 3D scanning and spatial machine learning. Projects span the whole semester and the objective can cover a variety of computer vision problems as large-scale 3D scanning, body tracking, face reconstruction and much more!
ContactM.Sc. Peter Kocsis,   M.Sc. Jiapeng Tang
DescriptionAdvanced Deep Learning. This lecture focuses on cutting edge Deep Learning techniques for computer vision with a heavy focus on Statistical Background, Recurrent Neural Networks (RNNs), and Generative Models (GANs). Part of the lecture is a semester-long project with a deep dive on modern DL methods.
ContactProf. Dr. Matthias Nießner
TAs: M.Sc. Dave Zhenyu Chen,  Dr. Yinyu Nie,  M.Sc. Barbara Rössle
DescriptionThis practical offers a deep stint into recent advances in Deep Learning and AI. Over the course we will carefully look into recent research highlights and implement hands-on state-of-the-art algorithms through engaging group projects.
ContactProf. Dr. Matthias Nießner
DescriptionThis colloquium invites prominent researchers to present new and exciting work across various fields in computer vision and artificial intelligence.
ContactM.Eng. Dejan Azinović
DescriptionThis is the research seminar of the Visual Computing Group. We discuss hot trends and ongoing work in computer vision, graphics, and machine learning.
ContactM.Sc. Norman Müller,   M.Sc. Shivangi Aneja

2021 Winter


DescriptionThis practical offers a deep-dive into recent advances in 3D scanning and spatial machine learning. Projects span the whole semester and the objective can cover a variety of computer vision problems as large-scale 3D scanning, body tracking, face reconstruction and much more!
ContactM.Sc. Aljaž Božič,   M.Sc. Pablo Palafox
DescriptionAdvanced Deep Learning. This lecture focuses on cutting edge Deep Learning techniques for computer vision with a heavy focus on Neural Rendering, Generative Adversarial Networks (GANs), Recurrent Neural Networks (RNNs), and many more topics related to the visual computing lab. Part of the lecture is a semester-long project with a deep dive on modern DL methods.
ContactProf. Dr. Matthias Nießner
TAs: M.Sc. Dave Zhenyu Chen,  M.Sc. Hao Yu,  M.Sc. Barbara Rössle
DescriptionThis practical offers a deep stint into recent advances in Deep Learning and AI. Over the course we will carefully look into recent research highlights and implement hands-on state-of-the-art algorithms through engaging group projects.
ContactProf. Dr. Matthias Nießner
DescriptionIntroduction to Deep Learning. This lecture focuses on modern machine learning techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Models (GANs).
ContactProf. Dr. Matthias Nießner
DescriptionThis colloquium invites prominent researchers to present new and exciting work across various fields in computer vision and artificial intelligence.
ContactM.Eng. Dejan Azinović
DescriptionThis is the research seminar of the Visual Computing Group. We discuss hot trends and ongoing work in computer vision, graphics, and machine learning.
ContactM.Sc. Norman Müller,   M.Sc. Shivangi Aneja

2021 Summer


DescriptionThis practical offers a deep-dive into recent advances in 3D scanning and spatial machine learning. Projects span the whole semester and the objective can cover a variety of computer vision problems as large-scale 3D scanning, body tracking, face reconstruction and much more!
ContactM.Sc. Aljaž Božič,   M.Sc. Pablo Palafox
DescriptionAdvanced Deep Learning. This lecture focuses on cutting edge Deep Learning techniques for computer vision with a heavy focus on Statistical Background, Recurrent Neural Networks (RNNs), and Generative Models (GANs). Part of the lecture is a semester-long project with a deep dive on modern DL methods.
ContactProf. Dr. Matthias Nießner
TAs: M.Sc. Dave Zhenyu Chen,  M.Sc. Hao Yu,  M.Sc. Barbara Rössle
DescriptionThis practical offers a deep stint into recent advances in Deep Learning and AI. Over the course we will carefully look into recent research highlights and implement hands-on state-of-the-art algorithms through engaging group projects.
ContactProf. Dr. Matthias Nießner
DescriptionIntroduction to Deep Learning. This lecture focuses on modern machine learning techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Models (GANs).
ContactProf. Dr. Matthias Nießner
TAs: M.Sc. Guy Gafni,  M.Sc. Manuel Dahnert
DescriptionThis colloquium invites prominent researchers to present new and exciting work across various fields in computer vision and artificial intelligence.
ContactM.Eng. Dejan Azinović
DescriptionThis is the research seminar of the Visual Computing Group. We discuss hot trends and ongoing work in computer vision, graphics, and machine learning.
ContactM.Sc. Norman Müller,   M.Sc. Shivangi Aneja

2020 Winter


DescriptionThis hands-on lecture focuses on cutting-edge 3D reconstruction approaches, including volumetric fusion approaches on implicit functions, face tracking, hand tracking, and much more! We also cover essential optimization techniques such as Gauss-Newton and Levenberg-Marquardt.
ContactDr. Justus Thies,   Prof. Dr. Angela Dai
TAs: M.Sc. Andrei Burov,  M.Sc. Felix AltenBerger
DescriptionThis practical offers a deep-dive into recent advances in 3D scanning and spatial machine learning. Projects span the whole semester and the objective can cover a variety of computer vision problems as large-scale 3D scanning, body tracking, face reconstruction and much more!
ContactDr. Justus Thies,   M.Sc. Manuel Dahnert,   M.Sc. Pablo Palafox
DescriptionAdvanced Deep Learning. This lecture focuses on cutting edge Deep Learning techniques for computer vision with a heavy focus on Statistical Background, Recurrent Neural Networks (RNNs), and Generative Models (GANs). Part of the lecture is a semester-long project with a deep dive on modern DL methods.
ContactProf. Dr. Matthias Nießner,   Prof. Dr. Laura Leal-Taixé
TAs: M.Sc. Yawar Siddiqui,  M.Sc. Dave Zhenyu Chen,  M.Sc. Guillem Braso,  M.Sc. Ismail Elezi
DescriptionThis practical offers a deep stint into recent advances in Deep Learning and AI. Over the course we will carefully look into recent research highlights and implement hands-on state-of-the-art algorithms through engaging group projects.
ContactProf. Dr. Matthias Nießner
DescriptionIntroduction to Deep Learning. This lecture focuses on modern machine learning techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Models (GANs).
ContactProf. Dr. Matthias Nießner,   Prof. Dr. Laura Leal-Taixé
TAs: M.Sc. Andreas Rössler,  M.Sc. Franziska Gerken
DescriptionThis is a virtual talk series on various topics in computer vision and artificial intelligence. Our invited speakers are experts in their field and have already received international recognition for their work.
ContactProf. Dr. Matthias Nießner,   M.Eng. Dejan Azinović
DescriptionThis is the research seminar of the Visual Computing Group. We discuss hot trends and ongoing work in computer vision, graphics, and machine learning.
ContactM.Sc. Norman Müller,   M.Sc. Christian Diller,   Dr. Justus Thies

2020 Summer


DescriptionThis hands-on lecture focuses on cutting-edge 3D reconstruction approaches, including volumetric fusion approaches on implicit functions, face tracking, hand tracking, and much more! We also cover essential optimization techniques such as Gauss-Newton and Levenberg-Marquardt.
ContactDr. Justus Thies,   Prof. Dr. Angela Dai
TAs: M.Eng. Dejan Azinović,  M.Sc. Manuel Dahnert
DescriptionThis practical offers a deep-dive into recent advances in 3D scanning and spatial machine learning. Projects span the whole semester and the objective can cover a variety of computer vision problems as large-scale 3D scanning, body tracking, face reconstruction and much more!
ContactDr. Justus Thies,   M.Sc. Andrei Burov,   M.Sc. Pablo Palafox
DescriptionAdvanced Deep Learning. This lecture focuses on cutting edge Deep Learning techniques for computer vision with a heavy focus on Statistical Background, Recurrent Neural Networks (RNNs), and Generative Models (GANs). Part of the lecture is a semester-long project with a deep dive on modern DL methods.
ContactProf. Dr. Matthias Nießner,   Prof. Dr. Laura Leal-Taixé
TAs: M.Sc. Ji Hou,  M.Sc. Dave Zhenyu Chen,  M.Sc. Tim Meinhardt,  M.Sc. Maxim Maximov
DescriptionThis practical offers a deep stint into recent advances in Deep Learning and AI. Over the course we will carefully look into recent research highlights and implement hands-on state-of-the-art algorithms through engaging group projects.
ContactProf. Dr. Matthias Nießner
DescriptionIntroduction to Deep Learning. This lecture focuses on modern machine learning techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Models (GANs).
ContactProf. Dr. Matthias Nießner,   Prof. Dr. Laura Leal-Taixé
TAs: M.Sc. Andreas Rössler,  M.Sc. Patrick Dendorfer
DescriptionThis is the research seminar of the Visual Computing Group. We discuss hot trends and ongoing work in computer vision, graphics, and machine learning.
ContactM.Sc. Norman Müller,   M.Sc. Christian Diller,   Dr. Justus Thies

2019 Winter


DescriptionThis hands-on lecture focuses on cutting-edge 3D reconstruction approaches, including volumetric fusion approaches on implicit functions, face tracking, hand tracking, and much more! We also cover essential optimization techniques such as Gauss-Newton and Levenberg-Marquardt.
ContactDr. Justus Thies,   Prof. Dr. Angela Dai
TAs: M.Eng. Dejan Azinović,  M.Sc. Manuel Dahnert
DescriptionThis practical offers a deep-dive into recent advances in 3D scanning and spatial machine learning. Projects span the whole semester and the objective can cover a variety of computer vision problems as large-scale 3D scanning, body tracking, face reconstruction and much more!
ContactDr. Justus Thies,   M.Eng. Armen Avetisyan,   M.Sc. Aljaž Božič
DescriptionAdvanced Deep Learning. This lecture focuses on cutting edge Deep Learning techniques for computer vision with a heavy focus on Statistical Background, Recurrent Neural Networks (RNNs), and Generative Models (GANs). Part of the lecture is a semester-long project with a deep dive on modern DL methods.
ContactProf. Dr. Matthias Nießner,   Prof. Dr. Laura Leal-Taixé
TAs: M.Sc. Ji Hou,  M.Sc. Dave Zhenyu Chen
DescriptionIntroduction to Deep Learning. This lecture focuses on modern machine learning techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Models (GANs).
ContactProf. Dr. Matthias Nießner,   Prof. Dr. Angela Dai
TAs: M.Sc. Andreas Rössler,  M.Sc. Yawar Siddiqui
DescriptionThis is the research seminar of the Visual Computing Group. We discuss hot trends and ongoing work in computer vision, graphics, and machine learning.
ContactM.Sc. Norman Müller,   M.Eng. Dejan Azinović,   Dr. Justus Thies

2019 Summer


DescriptionThis hands-on lecture focuses on cutting-edge 3D reconstruction approaches, including volumetric fusion approaches on implicit functions, face tracking, hand tracking, and much more! We also cover essential optimization techniques such as Gauss-Newton and Levenberg-Marquardt.
ContactDr. Justus Thies,   Prof. Dr. Angela Dai
TAs: M.Eng. Dejan Azinović,  M.Sc. Manuel Dahnert
DescriptionAdvanced Deep Learning. This lecture focuses on cutting edge Deep Learning techniques for computer vision with a heavy focus on Statistical Background, Recurrent Neural Networks (RNNs), and Generative Models (GANs). Part of the lecture is a semester-long project with a deep dive on modern DL methods.
ContactProf. Dr. Matthias Nießner,   Prof. Dr. Laura Leal-Taixé
TAs: M.Sc. Ji Hou,  M.Sc. Andreas Rössler,  M.Sc. Tim Meinhardt
DescriptionIntroduction to Deep Learning. This lecture focuses on modern machine learning techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Models (GANs).
ContactProf. Dr. Matthias Nießner,   Prof. Dr. Laura Leal-Taixé
TAs: M.Sc. Andreas Rössler,  M.Sc. Tim Meinhardt
DescriptionThis is the research seminar of the Visual Computing Group. We discuss hot trends and ongoing work in computer vision, graphics, and machine learning.
ContactM.Eng. Armen Avetisyan,   M.Sc. Aljaž Božič

2018 Winter


DescriptionThis hands-on lecture focuses on cutting-edge 3D reconstruction approaches, including volumetric fusion approaches on implicit functions, face tracking, hand tracking, and much more! We also cover essential optimization techniques such as Gauss-Newton and Levenberg-Marquardt.
ContactProf. Dr. Angela Dai,   Dr. Justus Thies
TAs: M.Eng. Dejan Azinović,  M.Eng. Armen Avetisyan
DescriptionIn this course, students will investigate recent research topics about 3D Scanning & Motion Capturing and present and summarize a chosen paper.
ContactM.Sc. Aljaž Božič,   M.Sc. Manuel Dahnert
DescriptionAdvanced Deep Learning. This lecture focuses on cutting edge Deep Learning techniques for computer vision with a heavy focus on Statistical Background, Recurrent Neural Networks (RNNs), and Generative Models (GANs). Part of the lecture is a semester-long project with a deep dive on modern DL methods.
ContactProf. Dr. Matthias Nießner,   Prof. Dr. Laura Leal-Taixé
TAs: M.Sc. Ji Hou,  M.Sc. Andreas Rössler,  M.Sc. Tim Meinhardt
DescriptionIntroduction to Deep Learning. This lecture focuses on modern machine learning techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Models (GANs).
ContactProf. Dr. Laura Leal-Taixé,   Prof. Dr. Matthias Nießner
TAs: M.Sc. Ji Hou,  M.Sc. Andreas Rössler,  M.Sc. Tim Meinhardt
DescriptionThis is the research seminar of the Visual Computing Group. We discuss hot trends and ongoing work in computer vision, graphics, and machine learning.
ContactDr. Justus Thies,   Prof. Dr. Matthias Nießner

2018 Summer


DescriptionThis hands-on lecture focuses on cutting-edge 3D reconstruction approaches, including volumetric fusion approaches on implicit functions, face tracking, hand tracking, and much more! We also cover essential optimization techniques such as Gauss-Newton and Levenberg-Marquardt.
ContactProf. Dr. Matthias Nießner
TAs: M.Sc. Aljaž Božič,  M.Eng. Armen Avetisyan
DescriptionIntroduction to Deep Learning for Computer Vision. This lecture focuses on modern machine learning techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Models (GANs).
ContactProf. Dr. Laura Leal-Taixé,   Prof. Dr. Matthias Nießner
TAs: M.Sc. Thomas Frerix,  M.Sc. Tim Meinhardt
DescriptionIntroduction to Deep Learning. This lecture focuses on modern machine learning techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Models (GANs).
ContactProf. Dr. Matthias Nießner,   Prof. Dr. Laura Leal-Taixé
TAs: M.Sc. Ji Hou,  M.Sc. Andreas Rössler,  M.Sc. Tim Meinhardt
DescriptionThis is the research seminar of the Visual Computing Group. We discuss hot trends and ongoing work in computer vision, graphics, and machine learning.
ContactDr. Justus Thies,   Prof. Dr. Matthias Nießner

2017 Winter


DescriptionThis hands-on lecture focuses on cutting-edge 3D reconstruction approaches, including volumetric fusion approaches on implicit functions, face tracking, hand tracking, and much more! We also cover essential optimization techniques such as Gauss-Newton and Levenberg-Marquardt.
ContactProf. Dr. Matthias Nießner
TAs: Dr. Justus Thies,  M.Sc. Aljaž Božič
DescriptionIntroduction to Deep Learning for Computer Vision. This lecture focuses on modern machine learning techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Models (GANs).
ContactProf. Dr. Matthias Nießner,   Prof. Dr. Laura Leal-Taixé
TAs: M.Sc. Thomas Frerix,  M.Sc. Ji Hou,  M.Sc. Andreas Rössler,  M.Sc. Tim Meinhardt
DescriptionThis is the research seminar of the Visual Computing Group. We discuss hot trends and ongoing work in computer vision, graphics, and machine learning.
ContactProf. Dr. Matthias Nießner

2017 Summer


DescriptionIntroduction to Deep Learning for Computer Vision. This lecture focuses on modern machine learning techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Models (GANs).
ContactProf. Dr. Laura Leal-Taixé,   Prof. Dr. Matthias Nießner
TAs: M.Sc. Thomas Frerix,  M.Sc. Tim Meinhardt
DescriptionIn this course, students will investigate recent research about machine learning techniques in the computer graphics area. Independent investigation for further reading, critical analysis, and evaluation of the topic are required.
ContactProf. Dr. Nils Thuerey,   Prof. Dr. Rüdiger Westermann,   Prof. Dr. Matthias Nießner,   Dr. Kiwon Um