RS2AD-LiDAR reconstructs vehicle LiDAR data from roadside observations via coordinate transformation, virtual LiDAR modeling and resampling, claimed as the first such method, with experiments showing improved object detection when mixed with real data.
In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
TCG-AR is a real-time multi-view AR system for trading card games using only commodity RGB cameras and synthetic training data.
ARCANE-PedSynth is a CARLA-based framework that generates synthetic multi-pedestrian datasets with behavioral crossing annotations by using hybrid AI-manual control to raise crossing rates and a 12-state FSM for diverse behaviors.
citing papers explorer
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RS2AD-LiDAR: End-to-End Autonomous Driving LiDAR Data Generation from Roadside Sensor Observations
RS2AD-LiDAR reconstructs vehicle LiDAR data from roadside observations via coordinate transformation, virtual LiDAR modeling and resampling, claimed as the first such method, with experiments showing improved object detection when mixed with real data.
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TCG-AR: Real-Time Multi-View Augmented Reality for Trading Card Game Streaming
TCG-AR is a real-time multi-view AR system for trading card games using only commodity RGB cameras and synthetic training data.
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ARCANE-PedSynth: Synthetic Multi-Pedestrian Datasets with Behavioural Crossing Annotations
ARCANE-PedSynth is a CARLA-based framework that generates synthetic multi-pedestrian datasets with behavioral crossing annotations by using hybrid AI-manual control to raise crossing rates and a 12-state FSM for diverse behaviors.