International audienceTo effectively manage and utilize the massive amount of visual data generated by the surging number of videos, decision-making systems must predict and reason about future outcomes. This paper proposes a novel online approach for video prediction that enables continual learning in the presence of new data, as periodic training of neural networks may not be practical. We utilize all predictions, including intermediate computations obtained during the inference process, to improve the performance of video prediction. To achieve this, we incorporate a weighting scheme in the loss that accounts for all the predictions during the learning process. Additionally, we leverage semantic segmentation to assess the performance of ...
International audienceThe ability to predict and therefore to anticipate the future is an important ...
Video prediction has developed rapidly after the booming of deep learning. As an important part of u...
In this paper, we introduce an approach for future frames prediction based on a single input image. ...
The ability to predict, anticipate and reason about future outcomes is a key component of intelligen...
While recent deep learning methods have made significant progress on the video prediction problem, m...
While great strides have been made in using deep learning algorithms to solve supervised learning ta...
Near-future prediction in videos has crucial impact on a wide range of practical applications which ...
International audienceThere is an inherent need for machines to have a notion of how entities within...
© 2020 IEEE We study a new research problem of probabilistic future frames prediction from a sequenc...
Anticipating actions and objects before they start or appear is a difficult problem in computer visi...
In many computer vision applications, machines will need to reason beyond the present, and predict t...
In this paper we present a conceptually simple but sur-prisingly powerful method for visual predicti...
Video prediction refers to predicting and generating future video frames given a set of consecutive ...
Deep neural networks are becoming central in several areas of computer vision. While there have been...
We present a novel deep learning architecture for probabilistic future prediction from video. We pre...
International audienceThe ability to predict and therefore to anticipate the future is an important ...
Video prediction has developed rapidly after the booming of deep learning. As an important part of u...
In this paper, we introduce an approach for future frames prediction based on a single input image. ...
The ability to predict, anticipate and reason about future outcomes is a key component of intelligen...
While recent deep learning methods have made significant progress on the video prediction problem, m...
While great strides have been made in using deep learning algorithms to solve supervised learning ta...
Near-future prediction in videos has crucial impact on a wide range of practical applications which ...
International audienceThere is an inherent need for machines to have a notion of how entities within...
© 2020 IEEE We study a new research problem of probabilistic future frames prediction from a sequenc...
Anticipating actions and objects before they start or appear is a difficult problem in computer visi...
In many computer vision applications, machines will need to reason beyond the present, and predict t...
In this paper we present a conceptually simple but sur-prisingly powerful method for visual predicti...
Video prediction refers to predicting and generating future video frames given a set of consecutive ...
Deep neural networks are becoming central in several areas of computer vision. While there have been...
We present a novel deep learning architecture for probabilistic future prediction from video. We pre...
International audienceThe ability to predict and therefore to anticipate the future is an important ...
Video prediction has developed rapidly after the booming of deep learning. As an important part of u...
In this paper, we introduce an approach for future frames prediction based on a single input image. ...