Titlebook: Computer Vision – ECCV 2024; 18th European Confer Aleš Leonardis,Elisa Ricci,Gül Varol Conference proceedings 2025 The Editor(s) (if applic

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Eigenmittel und deren Verwendung of human visual system and directly model the time dependencies among the fixations. Finally, a 3D Gaussian distribution is learned from each fixation embedding, from which the fixation position can be sampled. Evaluation on four panoramic eye-tracking datasets demonstrates that Pathformer3D outper

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Eigenmittel auf konsolidierter Basisdality fusion, thus achieving great robustness against sensor noises. By the time of paper submission, SparseLIF achieves state-of-the-art performance on the nuScenes dataset, ranking.on both validation set and test benchmark, outperforming all state-of-the-art 3D object detectors by a notable margi