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pro vyhledávání: '"Guhan, Pooja"'
Autor:
Bhattacharya, Uttaran, Rewkowski, Nicholas, Banerjee, Abhishek, Guhan, Pooja, Bera, Aniket, Manocha, Dinesh
Publikováno v:
IEEEVR 2021, pp. 1-10
We present Text2Gestures, a transformer-based learning method to interactively generate emotive full-body gestures for virtual agents aligned with natural language text inputs. Our method generates emotionally expressive gestures by utilizing the rel
Externí odkaz:
http://arxiv.org/abs/2101.11101
Autor:
Guhan, Pooja, Awasthi, Naman, McDonald, and Kathryn, Bussell, Kristin, Manocha, Dinesh, Reeves, Gloria, Bera, Aniket
We discuss MET, a learning-based algorithm proposed for perceiving a patient's level of engagement during telehealth sessions. We leverage latent vectors corresponding to Affective and Cognitive features frequently used in psychology literature to un
Externí odkaz:
http://arxiv.org/abs/2011.08690
Autor:
Bhattacharya, Uttaran, Rewkowski, Nicholas, Guhan, Pooja, Williams, Niall L., Mittal, Trisha, Bera, Aniket, Manocha, Dinesh
Publikováno v:
ISMAR, 2020, pp. 24-35
We present a novel autoregression network to generate virtual agents that convey various emotions through their walking styles or gaits. Given the 3D pose sequences of a gait, our network extracts pertinent movement features and affective features fr
Externí odkaz:
http://arxiv.org/abs/2010.01615
Autor:
Suryanarayanan, Parthasarathy, Tsou, Ching-Huei, Poddar, Ananya, Mahajan, Diwakar, Dandala, Bharath, Madan, Piyush, Agrawal, Anshul, Wachira, Charles, Samuel, Osebe Mogaka, Bar-Shira, Osnat, Kipchirchir, Clifton, Okwako, Sharon, Ogallo, William, Otieno, Fred, Nyota, Timothy, Matu, Fiona, Barros, Vesna Resende, Shats, Daniel, Kagan, Oren, Remy, Sekou, Bent, Oliver, Guhan, Pooja, Mahatma, Shilpa, Walcott-Bryant, Aisha, Pathak, Divya, Rosen-Zvi, Michal
The Coronavirus disease 2019 (COVID-19) global pandemic has transformed almost every facet of human society throughout the world. Against an emerging, highly transmissible disease with no definitive treatment or vaccine, governments worldwide have im
Externí odkaz:
http://arxiv.org/abs/2009.07057
Autor:
Mittal, Trisha, Guhan, Pooja, Bhattacharya, Uttaran, Chandra, Rohan, Bera, Aniket, Manocha, Dinesh
We present EmotiCon, a learning-based algorithm for context-aware perceived human emotion recognition from videos and images. Motivated by Frege's Context Principle from psychology, our approach combines three interpretations of context for emotion r
Externí odkaz:
http://arxiv.org/abs/2003.06692
With the advent of artificial intelligence and machine learning, humanoid robots are made to learn a variety of skills which humans possess. One of fundamental skills which humans use in day-to-day activities is performing tasks with coordination bet
Externí odkaz:
http://arxiv.org/abs/1805.03584
Publikováno v:
IEEE International Conference on Robotics and Biomimetics 2017
Real time calculation of inverse kinematics (IK) with dynamically stable configuration is of high necessity in humanoid robots as they are highly susceptible to lose balance. This paper proposes a methodology to generate joint-space trajectories of s
Externí odkaz:
http://arxiv.org/abs/1801.10425
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