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pro vyhledávání: '"Scofano, Luca"'
Autor:
Scofano, Luca, Sampieri, Alessio, Campari, Tommaso, Sacco, Valentino, Spinelli, Indro, Ballan, Lamberto, Galasso, Fabio
The success of collaboration between humans and robots in shared environments relies on the robot's real-time adaptation to human motion. Specifically, in Social Navigation, the agent should be close enough to assist but ready to back up to let the h
Externí odkaz:
http://arxiv.org/abs/2404.11327
Autor:
Flaborea, Alessandro, di Melendugno, Guido Maria D'Amely, Plini, Leonardo, Scofano, Luca, De Matteis, Edoardo, Furnari, Antonino, Farinella, Giovanni Maria, Galasso, Fabio
Promptly identifying procedural errors from egocentric videos in an online setting is highly challenging and valuable for detecting mistakes as soon as they happen. This capability has a wide range of applications across various fields, such as manuf
Externí odkaz:
http://arxiv.org/abs/2404.01933
Autor:
Hajij, Mustafa, Papillon, Mathilde, Frantzen, Florian, Agerberg, Jens, AlJabea, Ibrahem, Ballester, Ruben, Battiloro, Claudio, Bernárdez, Guillermo, Birdal, Tolga, Brent, Aiden, Chin, Peter, Escalera, Sergio, Fiorellino, Simone, Gardaa, Odin Hoff, Gopalakrishnan, Gurusankar, Govil, Devendra, Hoppe, Josef, Karri, Maneel Reddy, Khouja, Jude, Lecha, Manuel, Livesay, Neal, Meißner, Jan, Mukherjee, Soham, Nikitin, Alexander, Papamarkou, Theodore, Prílepok, Jaro, Ramamurthy, Karthikeyan Natesan, Rosen, Paul, Guzmán-Sáenz, Aldo, Salatiello, Alessandro, Samaga, Shreyas N., Scardapane, Simone, Schaub, Michael T., Scofano, Luca, Spinelli, Indro, Telyatnikov, Lev, Truong, Quang, Walters, Robin, Yang, Maosheng, Zaghen, Olga, Zamzmi, Ghada, Zia, Ali, Miolane, Nina
We introduce TopoX, a Python software suite that provides reliable and user-friendly building blocks for computing and machine learning on topological domains that extend graphs: hypergraphs, simplicial, cellular, path and combinatorial complexes. To
Externí odkaz:
http://arxiv.org/abs/2402.02441
Autor:
Papillon, Mathilde, Hajij, Mustafa, Jenne, Helen, Mathe, Johan, Myers, Audun, Papamarkou, Theodore, Birdal, Tolga, Dey, Tamal, Doster, Tim, Emerson, Tegan, Gopalakrishnan, Gurusankar, Govil, Devendra, Guzmán-Sáenz, Aldo, Kvinge, Henry, Livesay, Neal, Mukherjee, Soham, Samaga, Shreyas N., Ramamurthy, Karthikeyan Natesan, Karri, Maneel Reddy, Rosen, Paul, Sanborn, Sophia, Walters, Robin, Agerberg, Jens, Barikbin, Sadrodin, Battiloro, Claudio, Bazhenov, Gleb, Bernardez, Guillermo, Brent, Aiden, Escalera, Sergio, Fiorellino, Simone, Gavrilev, Dmitrii, Hassanin, Mohammed, Häusner, Paul, Gardaa, Odin Hoff, Khamis, Abdelwahed, Lecha, Manuel, Magai, German, Malygina, Tatiana, Ballester, Rubén, Nadimpalli, Kalyan, Nikitin, Alexander, Rabinowitz, Abraham, Salatiello, Alessandro, Scardapane, Simone, Scofano, Luca, Singh, Suraj, Sjölund, Jens, Snopov, Pavel, Spinelli, Indro, Telyatnikov, Lev, Testa, Lucia, Yang, Maosheng, Yue, Yixiao, Zaghen, Olga, Zia, Ali, Miolane, Nina
This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competition asked participants to provide open-source implementations of topo
Externí odkaz:
http://arxiv.org/abs/2309.15188
Autor:
Scofano, Luca, Sampieri, Alessio, Schiele, Elisabeth, De Matteis, Edoardo, Leal-Taixé, Laura, Galasso, Fabio
Scene-aware global human motion forecasting is critical for manifold applications, including virtual reality, robotics, and sports. The task combines human trajectory and pose forecasting within the provided scene context, which represents a signific
Externí odkaz:
http://arxiv.org/abs/2309.08947
Autor:
Scofano, Luca, Sampieri, Alessio, Re, Giuseppe, Almanza, Matteo, Panconesi, Alessandro, Galasso, Fabio
Publikováno v:
Neural Processing Letters, 2024
Forecasting players in sports has grown in popularity due to the potential for a tactical advantage and the applicability of such research to multi-agent interaction systems. Team sports contain a significant social component that influences interact
Externí odkaz:
http://arxiv.org/abs/2304.08272
Autor:
Rahman, Muhammad Rameez Ur, Scofano, Luca, De Matteis, Edoardo, Flaborea, Alessandro, Sampieri, Alessio, Galasso, Fabio
The task of collaborative human pose forecasting stands for predicting the future poses of multiple interacting people, given those in previous frames. Predicting two people in interaction, instead of each separately, promises better performance, due
Externí odkaz:
http://arxiv.org/abs/2304.05758
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