Seminar on Current Works in Computer Vision
Prof. Thomas BroxComputer Vision is a very active research field with many practical applications, for instance in quality control, robotics, or driver assistance systems. The goal of Computer Vision is to imitate the flexibility and robustness of the human visual system. Research has made significant progress in recent years particularly due to deep learning. Almost all research in Computer Vision has shifted to deep learning based methods.
In this seminar we will take a detailed look at some of the most interesting recent works. For each paper there will be one person, who performs a more detailed investigation of a research paper and its background and who will give a presentation. The presentation is followed by a discussion with all participants about the merits and limitations of the respective paper. You will learn to read and understand contemporary research papers, to give a good oral presentation, to ask questions, and to openly discuss a research problem.
In the poll of the introduction meeting it was decided to have this seminar as an online seminar in Zoom.
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Material:
Giving a good presentationProper scientific behavior
Slides of the introductory lecture
Powerpoint template for your presentation (optional)
Papers:
Date | Paper | Questions | Presenting student | Slides | Advisor |
T.B.A. | Weakly supervised object detection | questions | Dimitrios Chasanidis | Maria Bravo | |
17.6 | Network visualizations | questions | Paul Kull | slides | Philipp Schroeppel |
1.7 | Self-supervised object discovery | questions | Sai Bharath Chandra Gutha | slides | Silvio Galesso |
8.7 | Dataset for embodied learning | questions | Vasudha Venkatesan | slides | Max Argus |
15.7 | Image-text embeddings (CLIP) | questions | Bijay Gurung | Yassine Marrakchi | |
22.7 | Analysis of self-supervised learning | questions | Yubo Wang | Simon Schrodi | |
29.7 | Learning segmentation from image-text pairs | questions | Akshay Chandra Lagandula | Jan Bechtold |