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

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,DualBEV: Unifying Dual View Transformation with?Probabilistic Correspondences,orrespondences in one stage, DualBEV effectively bridges the gap between these strategies, harnessing their individual strengths. Our method achieves state-of-the-art performance without Transformer, delivering comparable efficiency to the LSS approach, with 55.2% mAP and 63.4% NDS on the nuScenes test set. Code is available at ..

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Conference proceedings 2025t learning, Object recognition, Image classification, Image processing, Object detection, Semantic segmentation, Human pose estimation, 3D reconstruction, Stereo vision, Computational photography, Neural networks, Image coding, Image reconstruction and Motion estimation..

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,OpenSight: A Simple Open-Vocabulary Framework?for?LiDAR-Based?Object?Detection,ectly transferring existing 2D open-vocabulary models with some known LiDAR classes for open-vocabulary ability, however, tends to suffer from over-fitting problems: The obtained model will detect the known objects, even presented with a novel category. In this paper, we propose OpenSight, a more ad

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,DailyDVS-200: A Comprehensive Benchmark Dataset for?Event-Based Action Recognition,range, minimal latency, and energy efficiency, setting them apart from conventional frame-based cameras. The distinctive capabilities of event cameras have ignited significant interest in the domain of event-based action recognition, recognizing their vast potential for advancement. However, the dev

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,On the?Topology Awareness and?Generalization Performance of?Graph Neural Networks,nant tool for learning representations of graph-structured data. A key feature of GNNs is their use of graph structures as input, enabling them to exploit the graphs’ inherent topological properties—known as the topology awareness of GNNs. Despite the empirical successes of GNNs, the influence of to

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,T-CorresNet: Template Guided 3D Point Cloud Completion with?Correspondence Pooling Query Generations often suffer from incompleteness due to limited perspectives, scanner resolution and occlusion. Therefore the prediction of missing parts performs a crucial task. In this paper, we propose a novel method for point cloud completion. We utilize a spherical template to guide the generation of the coa

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