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cs.CV2021
MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction
Patrick Dendorfer, Sven Elflein, Laura Leal-Taixé
Pedestrian trajectory prediction is challenging due to its uncertain and multimodal nature. While generative adversarial networks can learn a distribution over future trajectories,…
cs.LG2021★ 2 cited
On Out-of-distribution Detection with Energy-based Models
Sven Elflein, Bertrand Charpentier, Daniel Zügner +1
Several density estimation methods have shown to fail to detect out-of-distribution (OOD) samples by assigning higher likelihoods to anomalous data. Energy-based models (EBMs) are…