Zobrazeno 1 - 10
of 396
pro vyhledávání: '"Sabatini, Stefano"'
Autor:
Wang, Yixiao, Tang, Chen, Sun, Lingfeng, Rossi, Simone, Xie, Yichen, Peng, Chensheng, Hannagan, Thomas, Sabatini, Stefano, Poerio, Nicola, Tomizuka, Masayoshi, Zhan, Wei
Diffusion models are promising for joint trajectory prediction and controllable generation in autonomous driving, but they face challenges of inefficient inference steps and high computational demands. To tackle these challenges, we introduce Optimal
Externí odkaz:
http://arxiv.org/abs/2408.00766
Inspired by recent developments regarding the application of self-supervised learning (SSL), we devise an auxiliary task for trajectory prediction that takes advantage of map-only information such as graph connectivity with the intent of improving ma
Externí odkaz:
http://arxiv.org/abs/2210.04672
Traffic simulation has gained a lot of interest for quantitative evaluation of self driving vehicles performance. In order for a simulator to be a valuable test bench, it is required that the driving policy animating each traffic agent in the scene a
Externí odkaz:
http://arxiv.org/abs/2208.04803
While a lot of work has been carried on developing trajectory prediction methods, and various datasets have been proposed for benchmarking this task, little study has been done so far on the generalizability and the transferability of these methods a
Externí odkaz:
http://arxiv.org/abs/2205.07310
Autor:
Bonomini, Anna, Felicetti, Tommaso, Pacetti, Martina, Bertagnin, Chiara, Coletti, Alice, Giammarino, Federica, De Angelis, Marta, Poggialini, Federica, Macchiarulo, Antonio, Sabatini, Stefano, Mercorelli, Beatrice, Nencioni, Lucia, Vicenti, Ilaria, Dreassi, Elena, Cecchetti, Violetta, Tabarrini, Oriana, Loregian, Arianna, Massari, Serena
Publikováno v:
In European Journal of Medicinal Chemistry 5 November 2024 277
In this paper, we propose THOMAS, a joint multi-agent trajectory prediction framework allowing for an efficient and consistent prediction of multi-agent multi-modal trajectories. We present a unified model architecture for simultaneous agent future h
Externí odkaz:
http://arxiv.org/abs/2110.06607
In this paper, we propose GOHOME, a method leveraging graph representations of the High Definition Map and sparse projections to generate a heatmap output representing the future position probability distribution for a given agent in a traffic scene.
Externí odkaz:
http://arxiv.org/abs/2109.01827
In this paper, we propose HOME, a framework tackling the motion forecasting problem with an image output representing the probability distribution of the agent's future location. This method allows for a simple architecture with classic convolution n
Externí odkaz:
http://arxiv.org/abs/2105.10968
Autor:
Felicetti, Tommaso, Gwee, Chin Piaw, Burali, Maria Sole, Chan, Kitti Wing Ki, Alonso, Sylvie, Pismataro, Maria Chiara, Sabatini, Stefano, Barreca, Maria Letizia, Cecchetti, Violetta, Vasudevan, Subhash G., Manfroni, Giuseppe
Publikováno v:
In European Journal of Medicinal Chemistry 5 April 2023 252
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.