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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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楼主: onychomycosis
发表于 2025-3-28 17:12:49 | 显示全部楼层
,A Direct Approach to Viewing Graph Solvability,its usefulness in understanding real structure from motion graphs; we propose an algorithm for testing infinitesimal solvability and extracting components of unsolvable cases, that is more efficient than previous work; we set up an open question on the connection between infinitesimal solvability and solvability.
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, FunQA: Towards Surprising Video Comprehension,a response to visual stimuli; rather, it hinges on the human capacity to understand (and appreciate) commonsense violations depicted in these videos. We introduce ., a challenging video question answering (QA) dataset specifically designed to evaluate and enhance the depth of video reasoning based o
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4D Contrastive Superflows are Dense 3D Representation Learners,a process that is both costly and labor-intensive. To address this challenge from a data representation learning perspective, we introduce ., a novel framework designed to harness consecutive LiDAR-camera pairs for establishing spatiotemporal pretraining objectives. SuperFlow stands out by integrati
发表于 2025-3-29 19:26:03 | 显示全部楼层
,ItTakesTwo: Leveraging Peer Representations for Semi-supervised LiDAR Semantic Segmentation,velopment of semi-supervised learning (SSL) methods. However, such SSL approaches often concentrate on employing consistency learning only for individual LiDAR representations. This narrow focus results in limited perturbations that generally fail to enable effective consistency learning. Additional
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,Robust Fitting on a Gate Quantum Computer,ial time. Computer vision researchers have long been attracted to the power of quantum computers. Robust fitting, which is fundamentally important to many computer vision pipelines, has recently been shown to be amenable to gate quantum computing. The previous proposed solution was to compute Boolea
发表于 2025-3-30 06:42:54 | 显示全部楼层
,H-V2X: A Large Scale Highway Dataset for BEV Perception,ts. However, these datasets primarily focus on urban intersections and lack data on highway scenarios. Additionally, the perception tasks in the datasets are mainly MONO 3D due to limited synchronized data across multiple sensors. To bridge this gap, we propose Highway-V2X (H-V2X), the first large-s
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