Meet Lamarr at CVPR 2024

The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. It provides exceptional value for students, academics, and industry researchers. The Lamarr Institute will be represented by two outstanding workshops, with our Principal Investigators Prof. Dr. Jürgen Gall and Prof. Dr. Hildegard Kühne serving as co-organizers.

Workshop by Prof. Dr. Jürgen Gall: “Fifth International Workshop on Large Scale Holistic Video Understanding”

In recent years, the ability of computer systems to classify and analyze online videos has greatly improved. Significant advancements have been made in specific video recognition tasks, such as action and scene recognition. However, the comprehensive understanding of videos, known as holistic video understanding (HVU), has not received the attention it deserves. This workshop focuses on HVU, which includes recognizing scenes, objects, actions, attributes, and events in real-world videos. We are introducing our HVU dataset, organized hierarchically with a semantic taxonomy for holistic video understanding. Our goal is to create a comprehensive video benchmark that integrates the recognition of all semantic concepts and drives research in this area.
The workshop will be rounded off by keynotes from distinguished speakers from Meta, NUS, Microsoft and the UVA Deep Vision Lab.

Workshop by Prof. Dr. Hildegard Kühne: “MMFM2: The 2nd Workshop on What is Next in Multimodal Foundation Models?”

Multimodal Foundation Models (MMFMs) have shown unprecedented performance in many computer vision tasks. However, on some very specific tasks like document understanding, their performance is still underwhelming. To evaluate and improve these strong multi-modal models for the task of document image understanding, we harness a large amount of publicly available and privately gathered data and propose a challenge.

The workshop will be rounded off by keynotes from distinguished speakers from UW Madison, Google AI, and MIT EECS and a panel discussion.