CARLA-4D Visualizations for Revealing Occlusions with 4D Neural Fields

Description

Our model takes a point cloud video clip with 12 frames as input, and subsequently conditions a spatiotemporal neural field in order to predict output point clouds of the complete dynamic scene at a chosen moment in time. These longer videos are created by repeatedly applying the model over subsequent time windows.

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