Cross-View Geo-Localization (CVGL) with OpenStreetMap (OSM) performs well in structure-rich urban environments but collapses in feature-sparse scenes such as rural roads. To study this failure mode, in this work, we introduce CV-FSS, a benchmark that pairs sequential panoramas from five rural regions with aligned OSM m...
Junwei Zheng, Yunyi Huang, Ruize Dai et al.· 1 citation
Vision-language-action (VLA) models built on pretrained vision-language models have demonstrated strong performance across diverse robotic manipulation tasks. However, VLA models that directly map current 2D observations to actions often lack sufficient spatial and temporal understanding, limiting their performance in...
Zhi-Yuan Gao, Di Wen, Yan Zhan et al.· 0 citations
This work forms Progressive Cross-view Video Geo-localization (PCVG) as a deployment-oriented extension and evaluation protocol of CVG, enabling localization under varying temporal budgets, prefix-based inference, random-start evaluation, and long-range localization with interruptions.
Zi-Chao Zeng, Weijia Fan, Yu-Fan Chen et al.· 0 citations
A cross-domain egocentric video question answering benchmark designed to evaluate whether multimodal large language models can generalize beyond common daily-life scenarios, and two official Codabench tracks.
Yu-Qian Fu, Tianwen Qian, Yanjun Li et al.· 0 citations
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