https://cvg.cit.tum.de/ 2026-04-23T10:50:13+00:00 FeedCreator 1.8 (info@mypapit.net) 2021-10-18T11:24:46+00:00 2021-10-18T11:24:46+00:00 https://cvg.cit.tum.de/teaching/ws2021/bdlstnc_ws2021?rev=1634556286&do=diff Anonymous anonymous@undisclosed.example.com ---------- Seminar: Beyond Deep Learning: Selected Topics on Novel Challenges (5 ECTS) Winter Semester 2021/2022, TU München Organizers: Christian Tomani, Yuesong Shen, Prof. Dr. Daniel Cremers E-Mail: <bdlstnc-ws21@vision.in.tum.de> News In order for participants to get matched to a topic, please send us an email to <bdlstnc-ws21@vision.in.tum.de> with the title “[Topic_Matching] <Firstname> <Lastname>”, and attach a filled topic preference form (rename to "firstname_lastname.xlsx") un…

---------- Seminar: Beyond Deep Learning: Selected Topics on Novel Challenges (5 ECTS) Winter Semester 2021/2022, TU München Organizers: Christian Tomani, Yuesong Shen, Prof. Dr. Daniel Cremers E-Mail: <bdlstnc-ws21@vision.in.tum.de> News In order for participants to get matched to a topic, please send us an email to <bdlstnc-ws21@vision.in.tum.de> with the title “[Topic_Matching] <Firstname> <Lastname>”, and attach a filled topic preference form (rename to "firstname_lastname.xlsx") un…

2022-01-24T18:03:05+00:00 2022-01-24T18:03:05+00:00 https://cvg.cit.tum.de/teaching/ws2021/create_dl?rev=1643047385&do=diff Anonymous anonymous@undisclosed.example.com ---------- Practical Course: Creation of Deep Learning Methods (10 ECTS) Winter Semester 2021/2022, TU München This is the winter semester 2021/2022 course. For the summer semester 2022 course, see here. Please send applications (including learning goals, programming skills description, code, grade transcripts - see preliminary meeting slides) to create-dl[at]vision.in.tum.de

---------- Practical Course: Creation of Deep Learning Methods (10 ECTS) Winter Semester 2021/2022, TU München This is the winter semester 2021/2022 course. For the summer semester 2022 course, see here. Please send applications (including learning goals, programming skills description, code, grade transcripts - see preliminary meeting slides) to create-dl[at]vision.in.tum.de

2022-01-24T18:02:52+00:00 2022-01-24T18:02:52+00:00 https://cvg.cit.tum.de/teaching/ws2021/dlpractice?rev=1643047372&do=diff Anonymous anonymous@undisclosed.example.com ---------- Practical Course: Hands-on Deep Learning for Computer Vision and Biomedicine (10 ECTS) Winter Semester 2021/2022, TU München This is the winter semester 2021/2022 course. For the summer semester 2022 course, see here. Please send applications (including learning goals, programming skills description, code, grade transcripts - see preliminary meeting slides) to dlpractice[at]vision.in.tum.de

---------- Practical Course: Hands-on Deep Learning for Computer Vision and Biomedicine (10 ECTS) Winter Semester 2021/2022, TU München This is the winter semester 2021/2022 course. For the summer semester 2022 course, see here. Please send applications (including learning goals, programming skills description, code, grade transcripts - see preliminary meeting slides) to dlpractice[at]vision.in.tum.de

2022-07-15T11:40:46+00:00 2022-07-15T11:40:46+00:00 https://cvg.cit.tum.de/teaching/ws2021/intellisys_ws2021?rev=1657885246&do=diff Anonymous anonymous@undisclosed.example.com Practical Course: Learning For Self-Driving Cars and Intelligent Systems (10 ECTS) Winter Semester 2021/22, TU München Organizers: Qadeer Khan, Mariia Gladkova Correspondence Please forward any queries related to the lab to: <intellisys-ws21.vision.in@tum.de>. Course Registration Assignment to the lab is done via the

Practical Course: Learning For Self-Driving Cars and Intelligent Systems (10 ECTS) Winter Semester 2021/22, TU München Organizers: Qadeer Khan, Mariia Gladkova Correspondence Please forward any queries related to the lab to: <intellisys-ws21.vision.in@tum.de>. Course Registration Assignment to the lab is done via the

2021-08-06T09:54:25+00:00 2021-08-06T09:54:25+00:00 https://cvg.cit.tum.de/teaching/ws2021/seminar_3d_generative_models?rev=1628243665&do=diff Anonymous anonymous@undisclosed.example.com ---------- Seminar: 3D Generative Models Introduction A generative model, as the name suggests, generates data based on a parameter. 3D generative models parametrically generate 3D data from a learned distribution of 3D shapes. The distribution is often learned from a 3D dataset. This area of research is now highly active due to the explosion of research in neural generative models such as variational auto-encoders, and generative adversarial networks.

---------- Seminar: 3D Generative Models Introduction A generative model, as the name suggests, generates data based on a parameter. 3D generative models parametrically generate 3D data from a learned distribution of 3D shapes. The distribution is often learned from a 3D dataset. This area of research is now highly active due to the explosion of research in neural generative models such as variational auto-encoders, and generative adversarial networks.

2021-09-28T11:54:26+00:00 2021-09-28T11:54:26+00:00 https://cvg.cit.tum.de/teaching/ws2021/seminar_accurate3d?rev=1632830066&do=diff Anonymous anonymous@undisclosed.example.com ---------- Seminar: An Overview of Methods for Accurate Geometry Reconstruction Seminar for computer science, games engineering and computational science and engineering (CSE) master students (IN2107). General Reconstruction of 3D geometry has always been a central application in Computer Vision research. This seminar will give an overview of the broad range of methods that can be applied to retrieve geometric information from sensor data. The focus will be on methods that are able to recons…

---------- Seminar: An Overview of Methods for Accurate Geometry Reconstruction Seminar for computer science, games engineering and computational science and engineering (CSE) master students (IN2107). General Reconstruction of 3D geometry has always been a central application in Computer Vision research. This seminar will give an overview of the broad range of methods that can be applied to retrieve geometric information from sensor data. The focus will be on methods that are able to recons…

2021-11-22T14:30:42+00:00 2021-11-22T14:30:42+00:00 https://cvg.cit.tum.de/teaching/ws2021/seminar_realtime3d?rev=1637591442&do=diff Anonymous anonymous@undisclosed.example.com ---------- Seminar: The Evolution of Motion Estimation and Real-time 3D Reconstruction Seminar IN2107, which is open to Master students from "computer science", "games engineering", "robotics, cognition, and intelligence", and other programs. Please consult TUMonline or your study coordinator for more information.

---------- Seminar: The Evolution of Motion Estimation and Real-time 3D Reconstruction Seminar IN2107, which is open to Master students from "computer science", "games engineering", "robotics, cognition, and intelligence", and other programs. Please consult TUMonline or your study coordinator for more information.

2022-03-09T03:42:22+00:00 2022-03-09T03:42:22+00:00 https://cvg.cit.tum.de/teaching/ws2021/visnav_ws2021?rev=1646797342&do=diff Anonymous anonymous@undisclosed.example.com Practical Course: Vision-based Navigation IN2106 (6h SWS / 10 ECTS) WS 2021, TU München Lecturers: Jason Chui, Simon Klenk Please direct questions to <visnav_ws2021@vision.in.tum.de> News * 2021-12-20: Our next meeting will be on 10.01.2022 * 2021-11-29: Please fill the google sheet in the material link for the phase2

Practical Course: Vision-based Navigation IN2106 (6h SWS / 10 ECTS) WS 2021, TU München Lecturers: Jason Chui, Simon Klenk Please direct questions to <visnav_ws2021@vision.in.tum.de> News * 2021-12-20: Our next meeting will be on 10.01.2022 * 2021-11-29: Please fill the google sheet in the material link for the phase2