Hidden Footprints: Learning Contextual Walkability from 3D Human Trails
@article{Sun2020HiddenFL, title={Hidden Footprints: Learning Contextual Walkability from 3D Human Trails}, author={Jin Sun and Hadar Averbuch-Elor and Q. Wang and Noah Snavely}, journal={ArXiv}, year={2020}, volume={abs/2008.08701} }
Predicting where people can walk in a scene is important for many tasks, including autonomous driving systems and human behavior analysis. Yet learning a computational model for this purpose is challenging due to semantic ambiguity and a lack of labeled data: current datasets only tell you where people are, not where they could be. We tackle this problem by leveraging information from existing datasets, without additional labeling. We first augment the set of valid, labeled walkable regions by… CONTINUE READING
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References
SHOWING 1-10 OF 33 REFERENCES
Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters
- Computer Science
- 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- 2017
- 41
- PDF
Binge Watching: Scaling Affordance Learning from Sitcoms
- Computer Science
- 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- 2017
- 32
- PDF
ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing
- Computer Science
- 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
- 2018
- 80
- PDF
Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond
- Computer Science, Mathematics
- ArXiv
- 2018
- 39
- PDF
Putting Humans in a Scene: Learning Affordance in 3D Indoor Environments
- Computer Science
- 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- 2019
- 25
- PDF
The Cityscapes Dataset for Semantic Urban Scene Understanding
- Computer Science
- 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- 2016
- 3,728
- PDF
Seeing What is Not There: Learning Context to Determine Where Objects are Missing
- Computer Science
- 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- 2017
- 17
- PDF
Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detection
- Computer Science
- 2017 IEEE International Conference on Computer Vision (ICCV)
- 2017
- 180
- PDF
Where and Who? Automatic Semantic-Aware Person Composition
- Computer Science
- 2018 IEEE Winter Conference on Applications of Computer Vision (WACV)
- 2018
- 17
- PDF