A differentiable motion forecasting model retrieves and refines interpretable trajectory anchors from a contrastively learned motion bank to improve transparency without sacrificing multi-modal accuracy.
Forecast-MAE: Self-supervised pre-training for motion forecasting with masked autoencoders.Proceedings of the IEEE/CVF Inter- national Conference on Computer Vision
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Recall to Predict: Grounding Motion Forecasting in Interpretable Motion Bank
A differentiable motion forecasting model retrieves and refines interpretable trajectory anchors from a contrastively learned motion bank to improve transparency without sacrificing multi-modal accuracy.