Vehicle-to-Infrastructure (V2I)
This is the dataset for paper VI-BEVSEG training and testing. For more details about the dataset structure, please refer to Nuscense or V2X-Sim. We only use the number 1 vehicle in the V2X-Sim dataset. Replace the folder in this dataset, and only keep the vehicle 1 six onboard cameras information, infrastructure camera information and their semantic camera information in 'sweeps' and 'samples' folder. Then replace the 'v1.0-trainval' folder with ours and put the h5 maps under V2X-Sim folder.
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This is the dataset for paper VI-BEVSEG training and testing. This dataset mostly inherits from V2X-Sim dataset. Follow the same dataset structure as the V2X-Sim dataset. Follow the V2X-Sim instruction to use. The only change we made is adding some 'h5' ground truth semantic maps. And we only keep the vehicle 1 camera information and infrastructure camera information.
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The TiHAN-V2X Dataset was collected in Hyderabad, India, across various Vehicle-to-Everything (V2X) communication types, including Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Infrastructure-to-Vehicle (I2V), and Vehicle-to-Cloud (V2C). The dataset offers comprehensive data for evaluating communication performance under different environmental and road conditions, including urban, rural, and highway scenarios.
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