MV2 Dataset MV2 is a multi view and multi vehicle urban driving dataset designed for research in novel view synthesis, neural rendering, 3D reconstruction, cross view scene understanding, and autonomous driving perception. The dataset contains synchronized image sequences captured from multiple viewpoints, including ground vehicles and aerial views, along with camera parameters required for geometry aware learning and rendering. The dataset is released for academic and research use. The full dataset is being made available here, and additional annotations such as segmentation masks for dynamic objects may be released in upcoming updates. Dataset Details Dataset Description MV2 focuses on challenging real world urban driving scenes with large viewpoint changes across vehicles and platforms. It is intended to support research on: Cross view novel view synthesis Multi vehicle and multi camera scene reconstruction Ground to aerial and aerial to ground rendering Geometry aware neural rendering Autonomous driving scene understanding Dynamic scene analysis in urban traffic environments Unlike single ego vehicle driving datasets, MV2 includes multiple observation platforms, making it usefu…
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