Modern Computer Vision Methods
This seminar course addresses recent methods in the domain of computer vision and their broader impact and application. A list of selected papers is proposed and will be studied and discussed. The advantages and drawback of modern computer vision methods are discussed and put in historic perspective in the field. Application domains include 2D and 3D object detection, image/video/spatial content segmentation, 3D reconstruction, multi-view imaging, sensor fusion, multi-modal imaging, vision for autonomous driving, camera and object pose estimation, SLAM, as well as deformable and rigid registration.
Dates and Topics
|15.07.2022||Preliminary Course Meeting||Slides|
|17.10.2022||- no session due to Welcome@TUM event -|
|24.10.2022||Introduction Session||Intro Slides Projects|
|07.11.2022||CVPR Break (Individual Preparation)|
|14.11.2022||Slot to meet with Supervisor|
|21.11.2022||Slot to meet with Supervisor|
|28.11.2022||Object Poses + Robotic Grasping||Gen6D TransGrasp|
|05.12.2022||Neural Fields: NeRF Enhancements + Semantics||Depth Priors Panoptic Fields|
|12.12.2022||Invited Talk by Steven McDonagh, Huawei on Tackling modality, data distribution challenges for real world Computer Vision||Google Scholar|
|09.01.2023||3D Reconstruction + Manipulation||ShapeFormer 3D Recon CLIP-NeRF|
|16.01.2023||Scene Mapping & High-Level Understanding||NICE-SLAM Commonsense|
|23.01.2023||Point Cloud Registration||GeoTransformer Lepard|
|30.01.2023||Deformable Shapes||KeyTR Neural Flow|
|06.02.2023||Invited Talk by Fabian Manhardt, Google on 3D Object Understanding||Google Scholar|
List of Topics and Material
For the application, please sent us your motivation (+ previous experience / CV / transcript in the field to increase your chances for matching) via e-mail to:
firstname.lastname@example.org (Application Deadline: July 26, 2022)
Please also register in the TUM matching system for the course. Keep in mind that your chances to be assigned to the course increase if you give it a higher rank in your choices. For further details about how the matching system works and its schedule please check this website.
We select appropriate candidates based on their background, interests, and motivation.