The system image of nvidai xavier will be available soon.
The assembly body is meant to hold the LiDAR and the camera in place so that the extrinsic calibration results can be reused, which can be readily done by manufacturing
factories using open source manufacturing designs.
Download assembly body
The data is organized as the following readme for each scene.
We collected 3D dynamic data of traffic scenes by 4 slave nodes set up at the four corners of a street crossroad, where many vehicles and pedestrians moved across the scene. We provided 4, 000 frames with 3D bounding box annotations of cars, cyclists, and pedestrians in the central area of the crossroad.
Readme for crossroads scene
To evaluate the performance of long-term objects tracking, we collected data of multiple persons moving for a long time in the plaza and rarely leaving,
for 1200 frames in the day and 1200 frames at night. The persons are free to move and interact with others,
which results in a lot of occlusions and intersected trajectories, causing great difficulties for single-view data.
Readme for multi_person_day
Multi person scene for day
Readme for multi_person_night
Multi person scene at night
The implementation of the baselines is available at our github repository. [link]
Meng Zhang, Wenxuan Guo, Bohao Fan, Yifan Chen, Jianjiang Feng, and Jie Zhou, “A Flexible Multi-view Multi-modal Imaging System for Large-Scale Outdoor Scenes”, 3DV, 2022