arXiv Machine Learning
Jul 7
Open-Weather Robust 3D Detection via Dual-Critic Diffusion Alignment
arXiv:2607. 01983v1 Announce Type: cross Abstract: Robust 3D object detection under adverse weather remains a critical hurdle for autonomous driving.
Multi-Sensor Alignment for Weather Simulations
arXiv:2607. 25612v1 Announce Type: new Abstract: Perception tasks for autonomous vehicles need to work satisfactorily in adverse weather conditions.
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arXiv AI
Jun 3
FRED: A Multi-Modal Autonomous Driving Dataset for Flooded Road Environments
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.
arXiv Machine Learning
Jun 30
Road Maps as Free Geometric Priors: Weather-Invariant Drone Geo-Localization with GeoFuse
arXiv:2605. 14925v2 Announce Type: replace-cross Abstract: Drone-view geo-localization aims to match a query drone image, often captured under adverse weather conditions (e.
arXiv AI
Jun 12
Heterogeneous LiDAR Early Fusion and Learned Re-Ranking Strategy for Robust Long-Term Place Recognition in Unstructured Environments
arXiv:2606. 13503v1 Announce Type: cross Abstract: Robust localization in unstructured environments, such as agricultural fields, is a critical challenge for autonomous systems.
arXiv AI
Jun 30
Semantic-Aware, Physics-Informed, Geometry-Grounded Weather Video Synthesis
arXiv:2606. 29020v1 Announce Type: cross Abstract: Weather synthesis aims to add weather effects to input videos while preserving scene identity, structure, and motion.
arXiv Machine Learning
Jun 10
WHU-Infra3D: A Full-stack Multi-modal Dataset and Benchmark for 3D Roadside Infrastructure Inventory
arXiv:2606. 09882v1 Announce Type: cross Abstract: The paradigm of digital twin cities is shifting from coarse visual mapping toward more precise and actionable digitization of urban assets.
arXiv AI
Jul 28
ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness
arXiv:2607. 23537v1 Announce Type: new Abstract: Autonomous driving under adverse weather remains a critical challenge, yet existing vision-language benchmarks mainly evaluate under standard conditions, synthetic corruptions, or single modality.
arXiv AI
Jul 23
D3VL: Understanding Driving Scenes from 3D Time Series Data and Video with Language Models
arXiv:2607. 19528v1 Announce Type: cross Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have triggered the development of end-to-end MLLMs for autonomous driving.
arXiv Machine Learning
Aug 4
Breaking the Statistical Similarity Trap in Extreme Convection Detection
arXiv:2509. 09195v2 Announce Type: replace Abstract: Current evaluation metrics for deep learning weather models create a "Statistical Similarity Trap", rewarding blurry predictions while missing rare, high-impact events.
arXiv Machine Learning
Jun 10
PhysMetrics.Weather: An Evaluation Framework for Physical Consistency in ML Weather Models
arXiv:2606. 10642v1 Announce Type: new Abstract: Machine learning weather prediction (MLWP) models have achieved impressive forecasting performance at a small fraction of the computational costs required for traditional physics-based methods.
arXiv AI
Jun 9
AQIFormer: A Transformer-Based Multi-View Architecture for Cross-City Air Quality Classification
arXiv:2606. 07648v1 Announce Type: cross Abstract: Air pollution represents one of the most critical environmental and public health challenges globally, with traditional sensor-based monitoring systems facing significant scalability and economic constraints.
arXiv Machine Learning
Jun 11
Urban Heat MiniCubes: An AI-Ready dataset for urban heat research
arXiv:2606. 11534v1 Announce Type: cross Abstract: Urban heat is amplified by impermeable surfaces and heterogeneous built environments, yet street-level variability remains difficult to quantify because multi-sensor observations are rarely available in consistent, analysis-ready form at the necessary spatiotemporal scales.