Multi-modality data from different sensors provides rich complementary information for 3D perception, becoming an essential component in reliable autonomous driving systems. Current research typically designs intricate and complex fusion strategies to integrate information from multimodal data on a unified bird's-eye-view (BEV) feature map for the joint learning of multiple perception tasks.
Estimating 3D geometry in underwater environments presents unique challenges due to light attenuation, scattering, and the absence of large-scale, high-quality 3D annotations. Pioneering methods rely on massive dense annotations that are impractical in underwater settings.
arXiv:2608. 15790v1 Announce Type: new Abstract: Crevasse mapping from uncrewed aerial vehicle (UAV) imagery matters for glaciological research and for field safety in glaciated terrain.
By Steven Wallace, William D Harcourt, Richard Hann, Aiden Durrant, Somayajulu Sripada, Georgios Leontidis
arXiv:2606. 02341v1 Announce Type: cross Abstract: Underwater acoustic classification has a wide array of oceanic applications, but faces challenges due to an increasingly complex acoustic environment.
By Amirmohammad Mohammadi, Joshua Peeples, Alexandra Van Dine
arXiv:2605. 22018v2 Announce Type: replace-cross Abstract: The Flooded Road Environments Dataset (FRED) is, to our knowledge, the first multi-modal autonomous driving dataset specifically targeting the collection of data from scenarios involving water hazards on the road.
By Connor Malone, Sebastien Demmel, Sebastien Glaser
arXiv:2608. 17561v1 Announce Type: cross Abstract: The health of marine ecosystems is a critical indicator of global environmental change, yet the physical constraints of underwater observation and the intrinsic challenges of processing marine imagery severely limit the scalability of systematic monitoring.
By Cesar Borja, Breck A. McCollum, Jarret E. Byrnes, Kenneth Sebens, Ana C. Murillo
arXiv:2506. 22174v3 Announce Type: replace-cross Abstract: The transport industry has recently shown significant interest in unmanned surface vehicles (USVs), specifically for port and inland waterway transport.
By Bavo Lesy, Siemen Herremans, Robin Kerstens, Jan Steckel, Walter Daems, Siegfried Mercelis, Ali Anwar
arXiv:2606. 14562v1 Announce Type: cross Abstract: Sociable weaver nests function as complex ecological structures offering thermoregulatory microhabitats and sustaining diverse species; however, datasets used in prior studies lack fine-grained 3D structural detail.
By Constanza A. Molina Catricheo, Simon Boeder, Ting-Jia Guo, Giacomo May, Cl\'ement Berthelot, Devis Tuia, Friedrich Fedor Reinhard, Fabio Remondino, Benjamin Risse
arXiv:2607. 04453v1 Announce Type: cross Abstract: The assessment of planktonic standing stocks and microorganism structures is critical for understanding upper ocean biological processes.
By Abdelrahman Sayed Sayed, Pierre-Jean Meyer, Asgeir J. S{\o}rensen, Mohamed Ghazel
arXiv:2606. 10819v1 Announce Type: cross Abstract: RS-MLLMs enable natural-language understanding and spatial reasoning over earth observation imagery.
By Miaoxin Cai, Guanqun Wang, Wei Zhang, Guangyao Zhou, Yin Zhuang, Tong Zhang, Hao Wang, He Chen, Jun Li
arXiv:2606. 13503v1 Announce Type: cross Abstract: Robust localization in unstructured environments, such as agricultural fields, is a critical challenge for autonomous systems.
By Judith Vilella-Cantos, Juan Jos\'e Cabrera, M\'onica Ballesta, David Valiente, Luis Pay\'a
arXiv:2509. 12040v3 Announce Type: replace-cross Abstract: Open-Vocabulary Remote Sensing Image Segmentation (OVRSIS), an emerging task that adapts Open-Vocabulary Segmentation (OVS) to the remote sensing (RS) domain, remains underexplored due to the absence of a unified evaluation benchmark and the domain gap between natural and RS images.
By Bingyu Li, Haocheng Dong, Da Zhang, Zhiyuan Zhao, Junyu Gao, Xuelong Li