3DSNet: Unsupervised Shape-to-Shape 3D Style Transfer. - Mattia Segù; Margarita Grinvald; Roland Siegwart; Federico Tombari (CoRR, 2020)

Depth-Aware Action Recognition: Pose-Motion Encoding through Temporal Heatmaps. - Mattia Segù; Federico Pirovano; Gianmario Fumagalli; Amedeo Fabris (CoRR, 2020)

A General Framework for Uncertainty Estimation in Deep Learning. - Antonio Loquercio; Mattia Segù; Davide Scaramuzza 001 (IEEE Robotics Autom. Lett., 2020)

On the Practicality of Deterministic Epistemic Uncertainty. - Janis Postels; Mattia Segù; Tao Sun 019; Luc Van Gool; Fisher Yu 001; Federico Tombari (CoRR, 2021)

SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation. - Tao Sun 019; Mattia Segù; Janis Postels; Yuxuan Wang; Luc Van Gool; Bernt Schiele; Federico Tombari; Fisher Yu 001 (CVPR, 2022)

Generative Cooperative Learning for Unsupervised Video Anomaly Detection. - Muhammad Zaigham Zaheer; Arif Mahmood; Muhammad Haris Khan; Mattia Segù; Fisher Yu 001; Seung-Ik Lee (CVPR, 2022)

On the Practicality of Deterministic Epistemic Uncertainty. - Janis Postels; Mattia Segù; Tao Sun 019; Luca Daniel Sieber; Luc Van Gool; Fisher Yu 001; Federico Tombari (ICML, 2022)

Normalization Perturbation: A Simple Domain Generalization Method for Real-World Domain Shifts. - Qi Fan; Mattia Segù; Yu-Wing Tai; Fisher Yu 001; Chi-Keung Tang; Bernt Schiele; Dengxin Dai (CoRR, 2022)

COOLer: Class-Incremental Learning for Appearance-Based Multiple Object Tracking. - Zhizheng Liu; Mattia Segù; Fisher Yu 001 (DAGM, 2023)

DARTH: Holistic Test-time Adaptation for Multiple Object Tracking. - Mattia Segù; Bernt Schiele; Fisher Yu 001 (ICCV, 2023)

Towards Robust Object Detection Invariant to Real-World Domain Shifts. - Qi Fan; Mattia Segù; Yu-Wing Tai; Fisher Yu 001; Chi-Keung Tang; Bernt Schiele; Dengxin Dai (ICLR, 2023)

Batch normalization embeddings for deep domain generalization. - Mattia Segù; Alessio Tonioni; Federico Tombari (Pattern Recognit., 2023)

Know Your Neighbors: Improving Single-View Reconstruction via Spatial Vision-Language Reasoning. - Rui Li 054; Tobias Fischer 004; Mattia Segù; Marc Pollefeys; Luc Van Gool; Federico Tombari (CVPR, 2024)

Matching Anything by Segmenting Anything. - Siyuan Li 008; Lei Ke; Martin Danelljan; Luigi Piccinelli; Mattia Segù; Luc Van Gool; Fisher Yu 001 (CVPR, 2024)

UniDepth: Universal Monocular Metric Depth Estimation. - Luigi Piccinelli; Yung-Hsu Yang; Christos Sakaridis; Mattia Segù; Siyuan Li 008; Luc Van Gool; Fisher Yu 001 (CVPR, 2024)

SLAck: Semantic, Location, and Appearance Aware Open-Vocabulary Tracking. - Siyuan Li 008; Lei Ke; Yung-Hsu Yang; Luigi Piccinelli; Mattia Segù; Martin Danelljan; Luc Van Gool (ECCV (27), 2024)

Walker: Self-supervised Multiple Object Tracking by Walking on Temporal Appearance Graphs. - Mattia Segù; Luigi Piccinelli; Siyuan Li 008; Luc Van Gool; Fisher Yu 001; Bernt Schiele (ECCV (8), 2024)

UniK3D: Universal Camera Monocular 3D Estimation. - Luigi Piccinelli; Christos Sakaridis; Mattia Segù; Yung-Hsu Yang; Siyuan Li 008; Wim Abbeloos; Luc Van Gool (CVPR, 2025)

Semantic Library Adaptation: LoRA Retrieval and Fusion for Open-Vocabulary Semantic Segmentation. - Reza Qorbani; Gianluca Villani; Theodoros Panagiotakopoulos; Marc Botet Colomer; Linus Härenstam-Nielsen; Mattia Segù; Pier Luigi Dovesi; Jussi Karlgren; Daniel Cremers; Federico Tombari; Matteo Poggi (CVPR, 2025)

Samba: Synchronized Set-of-Sequences Modeling for Multiple Object Tracking. - Mattia Segù; Luigi Piccinelli; Siyuan Li 008; Yung-Hsu Yang; Luc Van Gool; Bernt Schiele (ICLR, 2025)

UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler. - Luigi Piccinelli; Christos Sakaridis; Yung-Hsu Yang; Mattia Segù; Siyuan Li 008; Wim Abbeloos; Luc Van Gool (CoRR, 2025)

3D-MOOD: Lifting 2D to 3D for Monocular Open-Set Object Detection. - Yung-Hsu Yang; Luigi Piccinelli; Mattia Segù; Siyuan Li 008; Rui Huang; Yuqian Fu; Marc Pollefeys; Hermann Blum; Zuria Bauer (CoRR, 2025)