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InterOCF reveals that effectively integrating 2D and 3D spatio-temporal dynamics can dramatically enhance the accuracy of occupancy forecasting for autonomous vehicles.
Transformer-based architectures can now outperform CNNs in multi-view crowd tracking, especially in large, complex real-world scenes, thanks to a novel view-ground interaction mechanism.
