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ECCV 2024 29 September, 09:00-13:00, Suite 8 MiCo, Milan Italy
ECCV 2024 29 September, 09:00-13:00, Suite 8 MiCo, Milan Italy
YM Associate Professor of Computer Science Columbia University
TL;DR His research focuses on training machines to interact with their environment, aiming to develop robust and versatile models for perception. His lab explores visual models that utilize large volumes of unlabeled data and are transferable across different tasks and modalities. Other interests include scene dynamics, sound and language and beyond, interpretable models, and perception for robotics.
Professor and Head of Division at the Linköping University
TL;DR His research covers a wide range of topics within Artificial Visual Systems (AVS): three-dimensional computer vision, computational imaging, object detection, tracking, and recognition, and robot vision and autonomous systems.
Research Scientist Naver AI LAB
TL;DR His main expertise lies in multimodal and self-supervised representation learning, with additional focus on enhancing user experience through human-computer interaction and on effectively communicating complex data insights through information visualization.
Accepted Papers in Proceedings Track
Accepted Papers in Proceedings Track
Maximally Separated Active Learning [pdf]
Tejaswi Kasarla, Abhishek Jha, Faye Tervoort, Rita Cucchiara, Pascal Mettes
Hyperbolic Metric Learning for Visual Outlier Detection [pdf]
Alvaro Gonzalez-Jimenez, Simone Lionetti, Dena Bazazian, Philippe Gottfrois, Fabian Gröger, Alexander Navarini, Marc Pouly
A Bottom-Up Approach to Class-Agnostic Image Segmentation [pdf] [supplementary]
Sebastian Dille, Ari Blondal, Sylvain Paris, Yagiz Aksoy
Adversarial Attacks on Hyperbolic Networks [pdf]
Max van Spengler, Jan Zahálka, Pascal Mettes
Hyperbolic Learning with Multimodal Large Language Models [pdf]
Paolo Mandica, Luca Franco, Konstantinos Kallidromitis, Suzanne Petryk, Fabio Galasso
Embedding Geometries of Contrastive Language-Image Pre-Training [pdf] [supplementary]
Jason C. Chou, Nahid Alam
Learning Multi-Manifold Embedding for Out-Of-Distribution Detection [pdf] [supplementary] Best Paper Award!
Jeng-Lin Li, Ming-Ching Chang, Wei-Chao Chen
ProxyDR: Deep Hyperspherical Metric Learning with Distance Ratio-Based Formulation [pdf]
Hyeongji Kim, Changkyu Choi, Michael C. Kampffmeyer, Terje Berge, Pekka Parviainen, Ketil Malde
Backward-Compatible Aligned Representations via an Orthogonal Transformation Layer [pdf]
Simone Ricci, Niccolò Biondi, Federico Pernici , Alberto Del Bimbo
Accepted papers in extended abstracts or published work Track
Accepted papers in extended abstracts or published work Track
Flattening the Parent Bias: Hierarchical Semantic Segmentation in the Poincaré Ball [pdf]
Simon Weber, Baris Zöngür, Nikita Araslanov, Daniel Cremers
FlagRep: A Stiefel-coordinate flag representation for hierarchical datasets [pdf]
Nathan Mankovich, Tolga Birdal
HyperSDFusion: Bridging Hierarchical Structures in Language and Geometry for Enhanced 3D Text2Shape Generation [pdf]
Zhiying Leng, Tolga Birdal, Federico Tombari
Hyp²Nav: Hyperbolic Planning and Curiosity for Crowd Navigation [pdf]
Guido Maria D'Amely di Melendugno, Alessandro Flaborea, Pascal Mettes, Fabio Galasso
NRDF: Neural Riemannian Distance Fields for Learning Articulated Pose Priors [pdf]
Yannan He, Garvita Tiwari, Tolga Birdal, Jan E. Lenssen, Gerard Pons-Moll
Accept the Modality Gap: An Exploration in the Hyperbolic Space [pdf]
Sameera Ramasinghe
Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning [pdf]
Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon
Cross-modal Scalable Hyperbolic Hierarchical Clustering [pdf]
Teng Long, Nanne van Noord
Binary Hyperbolic Embeddings [pdf]
Teng Long, Pascal Mettes, Nanne van Noord
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