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Graz University of Technology
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EPO achieves high geometric accuracy in 3D reconstructions without the computational burden of traditional feature extraction, making advanced 3D modeling feasible on consumer-grade devices.
FlowObject bridges the gap between generative priors and real-world observations, achieving unprecedented fidelity in 3D reconstruction from sparse views.
A new dataset of European landmarks offers researchers a challenging benchmark for training and evaluating 3D reconstruction pipelines, filling a critical gap in high-quality, diverse data.
By jointly learning edge structures and event-depth flow, LEAR unlocks more robust event camera localization from LiDAR, even when direct correspondence is unreliable.
