Zobrazeno 1 - 10
of 76
pro vyhledávání: '"Beyan, Cigdem"'
Autor:
Alameda-Pineda, Xavier, Addlesee, Angus, García, Daniel Hernández, Reinke, Chris, Arias, Soraya, Arrigoni, Federica, Auternaud, Alex, Blavette, Lauriane, Beyan, Cigdem, Camara, Luis Gomez, Cohen, Ohad, Conti, Alessandro, Dacunha, Sébastien, Dondrup, Christian, Ellinson, Yoav, Ferro, Francesco, Gannot, Sharon, Gras, Florian, Gunson, Nancie, Horaud, Radu, D'Incà, Moreno, Kimouche, Imad, Lemaignan, Séverin, Lemon, Oliver, Liotard, Cyril, Marchionni, Luca, Moradi, Mordehay, Pajdla, Tomas, Pino, Maribel, Polic, Michal, Py, Matthieu, Rado, Ariel, Ren, Bin, Ricci, Elisa, Rigaud, Anne-Sophie, Rota, Paolo, Romeo, Marta, Sebe, Nicu, Sieińska, Weronika, Tandeitnik, Pinchas, Tonini, Francesco, Turro, Nicolas, Wintz, Timothée, Yu, Yanchao
Despite the many recent achievements in developing and deploying social robotics, there are still many underexplored environments and applications for which systematic evaluation of such systems by end-users is necessary. While several robotic platfo
Externí odkaz:
http://arxiv.org/abs/2404.07560
Objects are crucial for understanding human-object interactions. By identifying the relevant objects, one can also predict potential future interactions or actions that may occur with these objects. In this paper, we study the problem of Short-Term O
Externí odkaz:
http://arxiv.org/abs/2308.08303
Gaze target detection aims to predict the image location where the person is looking and the probability that a gaze is out of the scene. Several works have tackled this task by regressing a gaze heatmap centered on the gaze location, however, they o
Externí odkaz:
http://arxiv.org/abs/2307.09662
This paper aims to address the unsupervised video anomaly detection (VAD) problem, which involves classifying each frame in a video as normal or abnormal, without any access to labels. To accomplish this, the proposed method employs conditional diffu
Externí odkaz:
http://arxiv.org/abs/2307.01533
In this technical report, we describe the Guided-Attention mechanism based solution for the short-term anticipation (STA) challenge for the EGO4D challenge. It combines the object detections, and the spatiotemporal features extracted from video clips
Externí odkaz:
http://arxiv.org/abs/2305.16066
Short-term action anticipation (STA) in first-person videos is a challenging task that involves understanding the next active object interactions and predicting future actions. Existing action anticipation methods have primarily focused on utilizing
Externí odkaz:
http://arxiv.org/abs/2305.12953
This paper investigates the performance of diffusion models for video anomaly detection (VAD) within the most challenging but also the most operational scenario in which the data annotations are not used. As being sparse, diverse, contextual, and oft
Externí odkaz:
http://arxiv.org/abs/2304.05841
This paper addresses the problem of anticipating the next-active-object location in the future, for a given egocentric video clip where the contact might happen, before any action takes place. The problem is considerably hard, as we aim at estimating
Externí odkaz:
http://arxiv.org/abs/2302.06358
This paper addresses the gaze target detection problem in single images captured from the third-person perspective. We present a multimodal deep architecture to infer where a person in a scene is looking. This spatial model is trained on the head ima
Externí odkaz:
http://arxiv.org/abs/2208.10822
Autor:
Franceschini, Riccardo, Fini, Enrico, Beyan, Cigdem, Conti, Alessandro, Arrigoni, Federica, Ricci, Elisa
Emotion recognition is involved in several real-world applications. With an increase in available modalities, automatic understanding of emotions is being performed more accurately. The success in Multimodal Emotion Recognition (MER), primarily relie
Externí odkaz:
http://arxiv.org/abs/2207.11482