DL |
Deep Learning |
CNN |
Convolutional Neural Network |
3DOR |
3D Object Recognition |
3DPR |
3D Place Recognition |
RoI |
Region of Interest |
R-CNN |
Region-based Convolutional Neural Network |
SSD |
Single Shot MultiBox Detector |
YOLO |
You Only Look Once |
PC |
Point Cloud |
AVOD |
Aggregate View Object Detection |
PG-Net |
Proposal Generation network |
PE-Net |
Parameter Estimation network (PE-Net) |
KITTI |
Karlsruhe Institute of Technology and Toyota Technological Institute |
HKUST |
Hong Kong University of Science and Technology |
KAIST |
Korea Advanced Institute of Science and Technology |
NYUD2 |
New York University Dataset version 2 |
NCLT |
The University of Michigan North Campus Long-Term Vision |
DDD17 |
DAVIS Driving Dataset 2017 |
sGD |
Stochastic Gradient Descent |
BBox |
Bounding Box |
ADV |
Autonomous Driving Vehicle |
GS3D |
3D Guidance and using the Surface feature |
SS3D |
Single-Stage Monocular 3D |
M3DSSD |
Monocular 3D Single Stage object Detector |
SRCNN |
Stereo Recurrent Convolutional Neural Network |
NMS |
Non-Maximum Suppression |
FV |
Front-View |
BEV |
Bird’s-Eye View |
SegVNet |
Segmentation-based Voxel Network |
VFE |
Voxel Feature Encoder |
LidarMTL |
Lidar-based multi-task learning
network |
IPOD |
Intensive Point-based Object Detector for Point Cloud |
FVNet |
Front-View proposal generation Network |
DPointNet |
Density-oriented Point Network |
GCNN |
Graph Convolutional Neural Network |
RGNet |
Relation Graph Network |
HGNet |
Hierarchical Graph Network |
S-AT GCN |
Spatial Attention Graph Convolution |
MV3D |
Multi-view 3D Network |
MS-CNN |
Multi Scale Convolutional Neural Network |
S-AT |
Spatial-Attention |
BEVLFVC |
Bird’s Eye View LIDAR point cloud and
Front View Camera image |
MVX-Net |
Multimodal Voxelnet for 3d object detection |
NetVLAD |
Network for Vector of Locally Aggregated Descriptors |
DGCNN |
Dynamic graph Convolutional Neural Network |
AUC |
Area Under Curve |
AP |
Average Precision |
LPD-Net |
Large-scale Place Description |