Plenary Speakers
Modeling in an Ego-Sensed World
Forecasting the rise of wearable devices equipped with audio-visual feeds and onboard spatial sensors, this talk will present novel approaches for generative and perception modelling in egocentric videos. The talk argues for new ways to foresee egocentric videos as partial observations of a dynamic 3D world, where objects are out of sight but not out of…
Biography
Dima Damen is a Professor of Computer Vision at the University of Bristol and Senior Research Scientist at Google DeepMind. Dima is currently an EPSRC Fellow (2020-2026), focusing her research interests in the automatic understanding of object interactions,…
Rethinking Multimodal AI Models: Beyond Accuracy, Towards Trust
The rapid adoption of Large Multimodal Models is reshaping smart technologies, while simultaneously raising fundamental questions about trust, safety and accountability. Moving beyond traditional performance metrics, real-world deployment demands a deeper understanding of model behavior under uncertainty, bias, and privacy constraints. This talk presents a…
Biography
Elisa Ricci is a Professor at the University of Trento and Head of the Research Unit Deep Visual Learning at Fondazione Bruno Kessler. Her research lies at the intersection of computer vision, deep learning, and robotics perception. She is interested in…
Is Computer Vision ready for Autonomous Systems?
Computer vision is, in many ways, finally working. We are witnessing a shift toward agents that can leverage the reasoning capabilities of large models, alongside major advances in 3D scene understanding and long term point tracking, even under severe occlusions. But what do these developments actually mean for the success of autonomous systems in the real…
Biography
Fatma Güney is an asstistant Professor at the Deptement of Computer Engineering at Koç University in Istanbul.Previously, I was a postdoctoral researcher in the Visual Geometry Group (VGG) at the University of Oxford, working with Andrea Vedaldi and Andrew…
Understanding Animals from Visual Data
Understanding animals from visual data is a complex challenge with important applications in ecology, veterinary science, robotics, and computer graphics. In this talk, I will present our work toward automatic 3D and 4D reconstruction of animals, focusing on the development of realistic and controllable animal models. I will show how these models can be…
Biography
Silvia Zuffi is a Senior Research Scientist at the IMATI (Institute of Applied Mathematics and Information Technologies) of the Italian National Research Council (CNR) in Milan. She holds a PhD in Computer Science from Brown University, where her thesis…