Pascal Mettes
Assistant Professor - University of Amsterdam
Computer vision
Hierarchical knowledge
Hyperbolic geometry
Me and my team focus on deep learning in hyperbolic space. Within deep learning, we tend to question all aspects of training neural networks, from architectures and optimization to data and tricks. The most fundamental assumption, namely to operate in Euclidean space, is however rarely questioned. We believe that opening our scope beyond Euclid opens an entirely new worlds for deep learning. Specifically, we focus on hyperbolic deep learning. Learning in hyperbolic space enables us to learn hierarchical representations, with stronger robustness (with respect to OOD and adversarial samples), more compactness, and with the possibility of incorporating prior knowledge. We also consider it the native space for vision-language models. In our lab, we are therefore spearheading hyperbolic deep learning through algorithmic advances, open-source developments, and international workshops, tutorials, and talks.
This page will highlight some success stories of our journey, including the first software library for hyperbolic learning, the first international tutorials and survey on hyperbolic learning for computer vision, and hyperbolic learning for various domains, ranging from image segmentation and social navigation to hierarchical classification and vision-language alignment.
[07-2024] "Hyp2Nav: Hyperbolic Planning and Curiosity for Crowd Navigation" accepted to IROS [pdf].
[06-2024] "Intriguing Properties of Hyperbolic Vision-Language Models" accepted to TMLR [pdf].
[05-2024] "Hyperbolic Random Forests" accepted to TMLR [pdf].
[05-2024] Workshop on Hyperbolic and Hyperspherical Learning for Computer Vision at ECCV 2024!
[04-2024] I am a keynote at the 1st Workshop on Human-Centered Vision and Media Technologies.
[04-2024] I am a keynote at the CV papers challenge workshop hosted by AIST, Tokyo.
[03-2024] Our survey on Hyperbolic Deep Learning in Computer Vision has been accepted to IJCV.
[01-2024] I will be a speaker at the Oxford Machine Learning Summer School 2024.
[12-2023] Guido D'Amely and Alessandro Flaborea (University of Sapienza) will be visiting for 3 months.
[10-2023] "Poincaré ResNet" accepted to ICCV 2023 [pdf].
[08-2023] "HypLL: The Hyperbolic Learning Library" is accepted to ACM Multimedia 2023.
[06-2023] HypLL: The Hyperbolic Learning Library is now available! [github] [pdf]
[06-2023] We are organizing a new tutorial on hyperbolic learning at CVPR 2023.
[06-2023] I am giving a keynote at the CVPR 2023 anti-UAV workshop.
[05-2023] Our survey on Hyperbolic Deep Learning in Computer Vision is available online.
[02-2023] The recordings of the ECCV 2022 hyperbolic tutorial is now available online.
Host: prof. Zeynep Akata
Host: prof. Shih-Fu Chang
Promotors: prof. Cees Snoek and prof. Arnold Smeulders
Code and pre-computed prototypes are available [here].
Pre-trained models can be downloaded by following the instructions [here].
Code and pre-computed prototypes are available [here].
The complete Video Water Dataset is available [here] (warning 14GB).