Tracking Emerges by Looking Around Static Scenes, with Neural 3D Mapping-Reference-Cited by-同舟云学术

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Tracking Emerges by Looking Around Static Scenes, with Neural 3D Mapping

Published:2020 Issue: Volume: Page:598-614
ISSN:0302-9743
Container-title:Computer Vision – ECCV 2020
language:
Short-container-title:

Author:

Harley Adam W.,Lakshmikanth Shrinidhi Kowshika,Schydlo Paul,Fragkiadaki Katerina

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-58574-7_36

Reference54 articles.

1. Agrawal, P., Carreira, J., Malik, J.: Learning to see by moving. In: ICCV (2015)

2. Bernardin, K., Elbs, A., Stiefelhagen, R.: Multiple object tracking performance metrics and evaluation in a smart room environment. In: Sixth IEEE International Workshop on Visual Surveillance, in Conjunction with ECCV, vol. 90, p. 91. Citeseer (2006)

3. Lecture Notes in Computer Science;L Bertinetto,2016

4. Brodski, A., Paasch, G.F., Helbling, S., Wibral, M.: The faces of predictive coding. J. Neurosci. 35(24), 8997–9006 (2015)

5. Lecture Notes in Computer Science;T Brox,2010

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2. Fast and Explicit Neural View Synthesis;2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2022-01

3. Video Autoencoder: self-supervised disentanglement of static 3D structure and motion;2021 IEEE/CVF International Conference on Computer Vision (ICCV);2021-10

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