MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction-Reference-Cited by-同舟云学术

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MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction

Published:2021-10 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE/CVF International Conference on Computer Vision (ICCV)
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Author:

Dendorfer Patrick¹,Elflein Sven¹,Leal-Taixe Laura¹

Affiliation:

1. Technical University Munich

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9709627/9709628/09711160.pdf?arnumber=9711160

Reference42 articles.

1. AdaGAN: Boosting generative models;tolstikhin;Neural Information Processing Systems,2017

2. Learning disconnected manifolds: a no GANs land;tanielian;Proceedings of Machine Learning and Systems,2020

3. Discrete Variational Autoencoders;tyler rolfe;International Conference on Learning Representations,2017

4. Learning Social Etiquette: Human Trajectory Understanding In Crowded Scenes

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