HoloVIC: Large-scale Dataset and Benchmark for Multi-Sensor Holographic Intersection and Vehicle-Infrastructure Cooperative

TL;DR

HoloVIC introduces a large-scale multi-sensor dataset for vehicle-infrastructure cooperation at intersections, enabling improved perception in autonomous driving through multi-sensor fusion and benchmarking of related tasks.

Contribution

This paper presents HoloVIC, a comprehensive multi-sensor dataset with annotations and benchmarks for multi-sensor holographic vehicle-infrastructure cooperation in complex traffic environments.

Findings

HoloVIC contains over 100,000 synchronized frames from multiple sensors.

The dataset includes diverse intersection layouts and sensor configurations.

Benchmarks for four key tasks are provided to advance research.

Abstract

Vehicle-to-everything (V2X) is a popular topic in the field of Autonomous Driving in recent years. Vehicle-infrastructure cooperation (VIC) becomes one of the important research area. Due to the complexity of traffic conditions such as blind spots and occlusion, it greatly limits the perception capabilities of single-view roadside sensing systems. To further enhance the accuracy of roadside perception and provide better information to the vehicle side, in this paper, we constructed holographic intersections with various layouts to build a large-scale multi-sensor holographic vehicle-infrastructure cooperation dataset, called HoloVIC. Our dataset includes 3 different types of sensors (Camera, Lidar, Fisheye) and employs 4 sensor-layouts based on the different intersections. Each intersection is equipped with 6-18 sensors to capture synchronous data. While autonomous vehicles pass through these intersections for collecting VIC data. HoloVIC contains in total on 100k+ synchronous frames from different sensors. Additionally, we annotated 3D bounding boxes based on Camera, Fisheye, and Lidar. We also associate the IDs of the same objects across different devices and consecutive frames in sequence. Based on HoloVIC, we formulated four tasks to facilitate the development of related research. We also provide benchmarks for these tasks.