SUSTech POINTS: A Portable 3D Point Cloud Interactive Annotation Platform System
暂无分享,去创建一个
E Li | Shuaijun Wang | Chengyang Li | Dachuan Li | Xiangbin Wu | Qi Hao | Chengyang Li | Shuaijun Wang | Qi Hao | Xiangbin Wu | E. Li | Dachuan Li
[1] Christoph Stiller,et al. PointAtMe: Efficient 3D Point Cloud Labeling in Virtual Reality , 2019, 2019 IEEE Intelligent Vehicles Symposium (IV).
[2] Markus Vincze,et al. Multi-label Point Cloud Annotation by Selection of Sparse Control Points , 2017, 2017 International Conference on 3D Vision (3DV).
[3] Andreas Geiger,et al. Are we ready for autonomous driving? The KITTI vision benchmark suite , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[4] Yi-Ting Chen,et al. The H3D Dataset for Full-Surround 3D Multi-Object Detection and Tracking in Crowded Urban Scenes , 2019, 2019 International Conference on Robotics and Automation (ICRA).
[5] Ruigang Yang,et al. The ApolloScape Open Dataset for Autonomous Driving and Its Application , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6] Antonio Capobianco,et al. Go'Then'Tag: A 3-D point cloud annotation technique , 2014, 2014 IEEE Symposium on 3D User Interfaces (3DUI).
[7] Jiaolong Yang,et al. Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[8] Qiang Xu,et al. nuScenes: A Multimodal Dataset for Autonomous Driving , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Kurt Keutzer,et al. LATTE: Accelerating LiDAR Point Cloud Annotation via Sensor Fusion, One-Click Annotation, and Tracking , 2019, 2019 IEEE Intelligent Transportation Systems Conference (ITSC).
[10] Akshay Rangesh,et al. 3D BAT: A Semi-Automatic, Web-based 3D Annotation Toolbox for Full-Surround, Multi-Modal Data Streams , 2019, 2019 IEEE Intelligent Vehicles Symposium (IV).