5 citations · 14 across the 8 of their papers we have counts for
9 papers
Hierarchical Prompt Learning for Hyperbolic Vision-Language Models
Andro Erdelez, Pascal Mettes, Behzad Bozorgtabar
Hyperbolic vision-language models (VLMs) represent image and text features in a geometry naturally suited to hierarchy, but their adaptation to downstream tasks has largely relied…
Fourier Self-Supervision for Fine-Grained Generalized Category Discovery
Sarah Rastegar, Mina Ghadimi Atigh, Pascal Mettes +2
Generalized Category Discovery aims to recognize known categories while identifying novel ones within unlabeled data. Existing methods, typically based on self-supervision and cont…
Hyperbolic Concept Bottleneck Models
Daniel Uyterlinde, Swasti Shreya Mishra, Pascal Mettes
Concept Bottleneck Models (CBMs) have become a popular approach to enable interpretability in neural networks by constraining classifier inputs to a set of human-understandable con…
Find the Cliffhanger: Multi-Modal Trailerness in Soap Operas
Carlo Bretti, Pascal Mettes, Hendrik Vincent Koops +2
Creating a trailer requires carefully picking out and piecing together brief enticing moments out of a longer video, making it a challenging and time-consuming task. This requires…
Hyperbolic Random Forests
Lars Doorenbos, Pablo Márquez-Neila, Raphael Sznitman +1
Hyperbolic space is becoming a popular choice for representing data due to the hierarchical structure - whether implicit or explicit - of many real-world datasets. Along with it co…
Hyperbolic Deep Learning in Computer Vision: A Survey
Pascal Mettes, Mina Ghadimi Atigh, Martin Keller-Ressel +2
Deep representation learning is a ubiquitous part of modern computer vision. While Euclidean space has been the de facto standard manifold for learning visual representations, hype…
Hyperbolic Image Segmentation
Mina GhadimiAtigh, Julian Schoep, Erman Acar +2
For image segmentation, the current standard is to perform pixel-level optimization and inference in Euclidean output embedding spaces through linear hyperplanes. In this work, we…
Zero-Shot Action Recognition from Diverse Object-Scene Compositions
Carlo Bretti, Pascal Mettes
This paper investigates the problem of zero-shot action recognition, in the setting where no training videos with seen actions are available. For this challenging scenario, the cur…
Hyperbolic Busemann Learning with Ideal Prototypes
Mina Ghadimi Atigh, Martin Keller-Ressel, Pascal Mettes
Hyperbolic space has become a popular choice of manifold for representation learning of various datatypes from tree-like structures and text to graphs. Building on the success of d…