Transfusion: Robust lidar-camera fusion for 3d object detection with transformers

X Bai, Z Hu, X Zhu, Q Huang, Y Chen… - Proceedings of the …, 2022 - openaccess.thecvf.com
LiDAR and camera are two important sensors for 3D object detection in autonomous driving.
Despite the increasing popularity of sensor fusion in this field, the robustness against inferior …

GD-MAE: generative decoder for MAE pre-training on lidar point clouds

H Yang, T He, J Liu, H Chen, B Wu… - Proceedings of the …, 2023 - openaccess.thecvf.com
Despite the tremendous progress of Masked Autoencoders (MAE) in developing vision tasks
such as image and video, exploring MAE in large-scale 3D point clouds remains …

Pvt-ssd: Single-stage 3d object detector with point-voxel transformer

H Yang, W Wang, M Chen, B Lin, T He… - Proceedings of the …, 2023 - openaccess.thecvf.com
Recent Transformer-based 3D object detectors learn point cloud features either from point-
or voxel-based representations. However, the former requires time-consuming sampling …

An Efficient Ungrouped Mask Method with Two Learnable Parameters for 3D Object Detection

S Guo, L Shi, X Jiang, P Lv, Q Liu, Y Hu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In 3D point cloud-based object detection, attention mechanism in Group-Free [1] learns
direct relationships between proposals and all seed points, providing each proposal with a …

An object detection method from 3D point clouds based on seed filtering

S Guo, J Liang, L Shi, X Jiang, Q Liu… - … on Robotics and …, 2022 - ieeexplore.ieee.org
3D object detection based on point clouds has important theoretical and application values.
As an innova-tive algorithm, VoteNet takes raw point clouds as input and uses a Hough vote …