Mattia Segù

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 21

Top Topics

Multiple Object Tracking

Cooperative Learning

Action Recognition

Top Venues

IEEE Robotics Autom. Lett.

Publications

Luigi Piccinelli, Yung-Hsu Yang, Christos Sakaridis, Mattia Segù, Siyuan Li, Luc Van Gool, Fisher Yu
UniDepth: Universal Monocular Metric Depth Estimation. CoRR (2024)
Siyuan Li, Lei Ke, Martin Danelljan, Luigi Piccinelli, Mattia Segù, Luc Van Gool, Fisher Yu
Matching Anything by Segmenting Anything. CoRR (2024)
Rui Li, Tobias Fischer, Mattia Segù, Marc Pollefeys, Luc Van Gool, Federico Tombari
Know Your Neighbors: Improving Single-View Reconstruction via Spatial Vision-Language Reasoning. CoRR (2024)
Qi Fan, Mattia Segù, Yu-Wing Tai, Fisher Yu, Chi-Keung Tang, Bernt Schiele, Dengxin Dai
Towards Robust Object Detection Invariant to Real-World Domain Shifts. ICLR (2023)
Mattia Segù, Alessio Tonioni, Federico Tombari
Batch normalization embeddings for deep domain generalization. Pattern Recognit. 135 (2023)
Mattia Segù, Bernt Schiele, Fisher Yu
DARTH: Holistic Test-time Adaptation for Multiple Object Tracking. ICCV (2023)
Mattia Segù, Bernt Schiele, Fisher Yu
DARTH: Holistic Test-time Adaptation for Multiple Object Tracking. CoRR (2023)
Zhizheng Liu, Mattia Segù, Fisher Yu
COOLer: Class-Incremental Learning for Appearance-Based Multiple Object Tracking. CoRR (2023)
Zhizheng Liu, Mattia Segù, Fisher Yu
COOLer: Class-Incremental Learning for Appearance-Based Multiple Object Tracking. DAGM (2023)
Tao Sun, Mattia Segù, Janis Postels, Yuxuan Wang, Luc Van Gool, Bernt Schiele, Federico Tombari, Fisher Yu
SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation. CVPR (2022)
Muhammad Zaigham Zaheer, Arif Mahmood, Muhammad Haris Khan, Mattia Segù, Fisher Yu, Seung-Ik Lee
Generative Cooperative Learning for Unsupervised Video Anomaly Detection. CoRR (2022)
Janis Postels, Mattia Segù, Tao Sun, Luca Daniel Sieber, Luc Van Gool, Fisher Yu, Federico Tombari
On the Practicality of Deterministic Epistemic Uncertainty. ICML (2022)
Tao Sun, Mattia Segù, Janis Postels, Yuxuan Wang, Luc Van Gool, Bernt Schiele, Federico Tombari, Fisher Yu
SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation. CoRR (2022)
Qi Fan, Mattia Segù, Yu-Wing Tai, Fisher Yu, Chi-Keung Tang, Bernt Schiele, Dengxin Dai
Normalization Perturbation: A Simple Domain Generalization Method for Real-World Domain Shifts. CoRR (2022)
Muhammad Zaigham Zaheer, Arif Mahmood, M. Haris Khan, Mattia Segù, Fisher Yu, Seung-Ik Lee
Generative Cooperative Learning for Unsupervised Video Anomaly Detection. CVPR (2022)
Janis Postels, Mattia Segù, Tao Sun, Luc Van Gool, Fisher Yu, Federico Tombari
On the Practicality of Deterministic Epistemic Uncertainty. CoRR (2021)
Mattia Segù, Margarita Grinvald, Roland Siegwart, Federico Tombari
3DSNet: Unsupervised Shape-to-Shape 3D Style Transfer. CoRR (2020)
Mattia Segù, Federico Pirovano, Gianmario Fumagalli, Amedeo Fabris
Depth-Aware Action Recognition: Pose-Motion Encoding through Temporal Heatmaps. CoRR (2020)
Mattia Segù, Alessio Tonioni, Federico Tombari
Batch Normalization Embeddings for Deep Domain Generalization. CoRR (2020)
Antonio Loquercio, Mattia Segù, Davide Scaramuzza
A General Framework for Uncertainty Estimation in Deep Learning. IEEE Robotics Autom. Lett. 5 (2) (2020)
Mattia Segù, Antonio Loquercio, Davide Scaramuzza
A General Framework for Uncertainty Estimation in Deep Learning. CoRR (2019)