Zobrazeno 1 - 10
of 1 785
pro vyhledávání: '"Zordan P"'
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Structural Engineering International; May2024, Vol. 34 Issue 2, p332-334, 3p
Autor:
Paola Zordan
Publikováno v:
Educação & Realidade, Vol 47 (2022)
Entrevista com Sandra Corazza
Externí odkaz:
https://doaj.org/article/43a04229a19f47e4a390e27222b94eff
Autor:
Liu, Hsueh-Ti Derek, Agrawala, Maneesh, Yuksel, Cem, Omernick, Tim, Misra, Vinith, Corazza, Stefano, McGuire, Morgan, Zordan, Victor
This paper presents a unified differentiable boolean operator for implicit solid shape modeling using Constructive Solid Geometry (CSG). Traditional CSG relies on min, max operators to perform boolean operations on implicit shapes. But because these
Externí odkaz:
http://arxiv.org/abs/2407.10954
Autor:
Benchekroun, Otman, Xie, Kaixiang, Liu, Hsueh-Ti Derek, Grinspun, Eitan, Andrews, Sheldon, Zordan, Victor
Traditional character animation specializes in characters with a rigidly articulated skeleton and a bipedal/quadripedal morphology. This assumption simplifies many aspects for designing physically based animations, like locomotion, but comes with the
Externí odkaz:
http://arxiv.org/abs/2405.18609
Autor:
Shen, Siyuan, Shao, Tianjia, Zhou, Kun, Jiang, Chenfanfu, Andrews, Sheldon, Zordan, Victor, Yang, Yin
We present a framework of elastic locomotion, which allows users to enliven an elastic body to produce interesting locomotion by prescribing its high-level kinematics. We formulate this problem as an inverse simulation problem and seek the optimal mu
Externí odkaz:
http://arxiv.org/abs/2405.14595
Autor:
Xu, Pei, Xie, Kaixiang, Andrews, Sheldon, Kry, Paul G., Neff, Michael, McGuire, Morgan, Karamouzas, Ioannis, Zordan, Victor
Publikováno v:
ACM Transactions on Graphics 42, 6, Article 112.1522 (December 2023)
Motivated by humans' ability to adapt skills in the learning of new ones, this paper presents AdaptNet, an approach for modifying the latent space of existing policies to allow new behaviors to be quickly learned from like tasks in comparison to lear
Externí odkaz:
http://arxiv.org/abs/2310.00239
Autor:
Dugan, Liam, Wadhawan, Anshul, Spence, Kyle, Callison-Burch, Chris, McGuire, Morgan, Zordan, Victor
Recent work in speech-to-speech translation (S2ST) has focused primarily on offline settings, where the full input utterance is available before any output is given. This, however, is not reasonable in many real-world scenarios. In latency-sensitive
Externí odkaz:
http://arxiv.org/abs/2306.01201
Publikováno v:
ACM Transactions on Graphics (August 2023)
We present a deep learning method for composite and task-driven motion control for physically simulated characters. In contrast to existing data-driven approaches using reinforcement learning that imitate full-body motions, we learn decoupled motions
Externí odkaz:
http://arxiv.org/abs/2305.03286
Autor:
Giulio Maria Menti, Matteo Bruzzone, Mauro Agostino Zordan, Patrizia Visentin, Andrea Drago, Marco dal Maschio, Aram Megighian
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Animals’ ability to orient and navigate relies on selecting an appropriate motor response based on the perception and integration of the environmental information. This is the case, for instance, of the optokinetic response (OKR) in Drosop
Externí odkaz:
https://doaj.org/article/f1b85721c9314dbb98e73636cd5fde69