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pro vyhledávání: '"Aliakbarian, Mohammad Sadegh"'
Autor:
Aliakbarian, Mohammad Sadegh, Saleh, Fatemeh Sadat, Salzmann, Mathieu, Petersson, Lars, Gould, Stephen, Habibian, Amirhossein
Human motion prediction is a stochastic process: Given an observed sequence of poses, multiple future motions are plausible. Existing approaches to modeling this stochasticity typically combine a random noise vector with information about the previou
Externí odkaz:
http://arxiv.org/abs/1908.00733
Autor:
Aliakbarian, Mohammad Sadegh, Saleh, Fatemeh Sadat, Salzmann, Mathieu, Fernando, Basura, Petersson, Lars, Andersson, Lars
Action anticipation is critical in scenarios where one needs to react before the action is finalized. This is, for instance, the case in automated driving, where a car needs to, e.g., avoid hitting pedestrians and respect traffic lights. While soluti
Externí odkaz:
http://arxiv.org/abs/1810.09044
Autor:
Saleh, Fatemeh Sadat, Aliakbarian, Mohammad Sadegh, Salzmann, Mathieu, Petersson, Lars, Alvarez, Jose M.
Training a deep network to perform semantic segmentation requires large amounts of labeled data. To alleviate the manual effort of annotating real images, researchers have investigated the use of synthetic data, which can be labeled automatically. Un
Externí odkaz:
http://arxiv.org/abs/1807.06132
Autor:
Saleh, Fatemeh Sadat, Aliakbarian, Mohammad Sadegh, Salzmann, Mathieu, Petersson, Lars, Alvarez, Jose M.
Pixel-level annotations are expensive and time-consuming to obtain. Hence, weak supervision using only image tags could have a significant impact in semantic segmentation. Recent years have seen great progress in weakly-supervised semantic segmentati
Externí odkaz:
http://arxiv.org/abs/1708.04400
Autor:
Saleh, Fatemeh Sadat, Aliakbarian, Mohammad Sadegh, Salzmann, Mathieu, Petersson, Lars, Alvarez, Jose M., Gould, Stephen
Pixel-level annotations are expensive and time consuming to obtain. Hence, weak supervision using only image tags could have a significant impact in semantic segmentation. Recently, CNN-based methods have proposed to fine-tune pre-trained networks us
Externí odkaz:
http://arxiv.org/abs/1706.02189
Autor:
Aliakbarian, Mohammad Sadegh, Saleh, Fatemeh Sadat, Salzmann, Mathieu, Fernando, Basura, Petersson, Lars, Andersson, Lars
In contrast to the widely studied problem of recognizing an action given a complete sequence, action anticipation aims to identify the action from only partially available videos. As such, it is therefore key to the success of computer vision applica
Externí odkaz:
http://arxiv.org/abs/1703.07023
Autor:
Aliakbarian, Mohammad Sadegh, Saleh, Fatemehsadat, Fernando, Basura, Salzmann, Mathieu, Petersson, Lars, Andersson, Lars
Action recognition and anticipation are key to the success of many computer vision applications. Existing methods can roughly be grouped into those that extract global, context-aware representations of the entire image or sequence, and those that aim
Externí odkaz:
http://arxiv.org/abs/1611.05520
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Publikováno v:
2013 21st Iranian Conference on Electrical Engineering (ICEE); 2013, p1-6, 6p