Our results show that the first gameplay video statistically significantly increases the positive affect of the participants and that both first and third videos statistically significantly decrease the negative affect. A user study is then conducted where participants are asked to answer a questionnaire measuring their positive and negative affect after watching each of the three gameplay videos – the explosions with the highest average interestingness, the explosions with the lowest average interestingness, the explosions with the highest interestingness predicted by the regressor – in counterbalanced order. A regressor is then built from the collected data whose input consists of a set of features representing effects due to an explosion and output indicates the average interestingness. Interestingness-rating data on TNT explosions are collected from a number of participants. This paper proposes a TNT-generation system in Science Birds, an Angry Birds clone, which is aimed to help spectators maintain healthy emotion.
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Our code and trained models are available at Warping rather than image warping as practiced inįlowNet2. (3) Our network owns an effective structureįor pyramidal feature extraction and embraces feature (2) We present a novelįlow regularization layer to ameliorate the issue of outliersĪnd vague flow boundaries by using a feature-driven localĬonvolution. Not only improves flow estimation accuracy through earlyĬorrection, but also permits seamless incorporation of descriptor Pyramid level through a lightweight cascaded network. We present a more effective flow inference approach at each That might have been missed in the current frameworks: (1) Is made possible by drilling down to architectural details Model size and 1.36 times faster in the running speed.
KITTI benchmarks, while being 30 times smaller in the This paper we present an alternative network that outperformsįlowNet2 on the challenging Sintel final pass and Network (CNN) for optical flow estimation, requires overġ60M parameters to achieve accurate flow estimation. Setting this up takes just a few minutes - Click here for instructions.FlowNet2, the state-of-the-art convolutional neural Visitors to your site will appreciate you offering them help with planning their vacation.
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