Autonomous Vehicles
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Benchmarks
ApolloCar3D
Most implemented
AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges
nuScenes: A multimodal dataset for autonomous driving
Flow: A Modular Learning Framework for Mixed Autonomy Traffic
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
LEAF: A Benchmark for Federated Settings
Papers
PiPS: Post-Hoc Prototypical Explanations for Interpretable Semantic Segmentation
With the increasing deployment of deep neural networks in critical systems, such as medical diagnostics and autonomous vehicles, ensuring their interpretability is crucial to building trust in decision-making systems. In…
Semantic SegmentationImage ClassificationObject LocalizationAutonomous VehiclesQuantifying Spectral Differences in Vehicle Kinematics Between Production Autonomous and Human-Driven Vehicles Across Driving Scenarios
Differences in vehicle kinematic characteristics between production autonomous vehicles (PAVs) and human-driven vehicles (HVs) have been limitedly investigated by empirical studies. Most recent studies rely on simulation…
Autonomous VehiclesDensity EstimationAutonomous DrivingRethinking Language's Role in Efficient VLA for Autonomous Vehicles: Toward Smarter, Trustworthy Driving
Vision-Language-Action (VLA) models are reshaping autonomous driving (AD) by unifying perception, reasoning, and control through language, enabling semantic grounding, interpretable decisions, and better long-tail genera…
Autonomous VehiclesAutonomous DrivingMarine Autonomous Vehicle Fleet Scheduling to Maximise Scientific Impact
The marine science community increasingly relies on Marine Autonomous Vehicles (MAVs) to collect the critical environmental data required to understand global ocean systems. However, as these operations scale, manually r…
Autonomous VehiclesVision-centric generative AI models: A software-hardware perspective
Vision generative artificial intelligence (AI) has emerged as one of the most rapidly advancing areas of deep learning. The explosion of multimodal models has made them widely associated with text-to-image applications r…
Autonomous VehiclesMIVIFI: Bridging Perspective and Fisheye Domains for Training Multi-View Fisheye Image Generation Models
Achieving 360° coverage is critical for the visual perception systems of autonomous vehicles. Fisheye cameras offer a cost-effective solution by enabling full surround coverage with as few as two sensors. However, existi…
Autonomous VehiclesImage Generation