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Patrick Dendorfer

3 accepted papers

2022

MOTCOM: The Multi-Object Tracking Dataset Complexity Metric

ECCV 2022poster

"There exists no comprehensive metric for describing the complexity of Multi-Object Tracking (MOT) sequences. This lack of metrics decreases explainability, complicates comparison of datasets, and reduces the conversation on tracker performance to a matter of leader board position. As a remedy, we p…

Cited by 2SourcePDFScholar
2022

Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking?

NeurIPS 2022accept

Recent developments in monocular multi-object tracking have been very successful in tracking visible objects and bridging short occlusion gaps, mainly relying on data-driven appearance models. While significant advancements have been made in short-term tracking performance, bridging longer occlusio…

2021

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

ICCV 2021poster

Pedestrian trajectory prediction is challenging due to its uncertain and multimodal nature. While generative adversarial networks can learn a distribution over future trajectories, they tend to predict out-of-distribution samples when the distribution of future trajectories is a mixture of multiple,…

Cited by 143PDFcodeScholar