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Found 4 papers, 1 papers with code
ActiveAnno3D - An Active Learning Framework for Multi-Modal 3D Object Detection
We propose ActiveAnno3D, an active learning framework to select data samples for labeling that are of maximum informativeness for training.
TUMTraf Event: Calibration and Fusion Resulting in a Dataset for Roadside Event-Based and RGB Cameras
To the best of our knowledge, no targetless calibration between event-based and RGB cameras can handle multiple moving objects, nor does data fusion optimized for the domain of roadside ITS exist.
A9 Intersection Dataset: All You Need for Urban 3D Camera-LiDAR Roadside Perception
Our dataset consists of 4. 8k images and point clouds with more than 57. 4k manually labeled 3D boxes.
A9-Dataset: Multi-Sensor Infrastructure-Based Dataset for Mobility Research
As part of the first set of data, which we describe in this paper, we provide camera and LiDAR frames from two overhead gantry bridges on the A9 autobahn with the corresponding objects labeled with 3D bounding boxes.
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