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

Patrick Dendorfer, Sven Elflein, Laura Leal-Taixé. MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction. In 2021 IEEE/CVF International Conference on Computer Vision, ICCV 2021, Montreal, QC, Canada, October 10-17, 2021. pages 13138-13147, IEEE, 2021. [doi]

@inproceedings{DendorferEL21,
  title = {MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction},
  author = {Patrick Dendorfer and Sven Elflein and Laura Leal-Taixé},
  year = {2021},
  doi = {10.1109/ICCV48922.2021.01291},
  url = {https://doi.org/10.1109/ICCV48922.2021.01291},
  researchr = {https://researchr.org/publication/DendorferEL21},
  cites = {0},
  citedby = {0},
  pages = {13138-13147},
  booktitle = {2021 IEEE/CVF International Conference on Computer Vision, ICCV 2021, Montreal, QC, Canada, October 10-17, 2021},
  publisher = {IEEE},
  isbn = {978-1-6654-2812-5},
}