103 citations · 183 across the 11 of their papers we have counts for
12 papers · 1 filter
TrajSSL: Trajectory-Enhanced Semi-Supervised 3D Object Detection
Philip Jacobson, Yichen Xie, Mingyu Ding +4
Semi-supervised 3D object detection is a common strategy employed to circumvent the challenge of manually labeling large-scale autonomous driving perception datasets. Pseudo-labeli…
DSLO: Deep Sequence LiDAR Odometry Based on Inconsistent Spatio-temporal Propagation
Huixin Zhang, Guangming Wang, Xinrui Wu +5
This paper introduces a 3D point cloud sequence learning model based on inconsistent spatio-temporal propagation for LiDAR odometry, termed DSLO. It consists of a pyramid structure…
Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection
Jinhyung Park, Chenfeng Xu, Shijia Yang +4
While recent camera-only 3D detection methods leverage multiple timesteps, the limited history they use significantly hampers the extent to which temporal fusion can improve object…
PreTraM: Self-Supervised Pre-training via Connecting Trajectory and Map
Chenfeng Xu, Tian Li, Chen Tang +5
Deep learning has recently achieved significant progress in trajectory forecasting. However, the scarcity of trajectory data inhibits the data-hungry deep-learning models from lear…
DetMatch: Two Teachers are Better Than One for Joint 2D and 3D Semi-Supervised Object Detection
Jinhyung Park, Chenfeng Xu, Yiyang Zhou +2
While numerous 3D detection works leverage the complementary relationship between RGB images and point clouds, developments in the broader framework of semi-supervised object recog…
VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results
Dawei Du, Longyin Wen, Pengfei Zhu +52
Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint.…