FSL-Survey[1] is a survey on Few-Shot Learning(FSL), which cotains 166 paper to review Few-Shot Learning. They categorize FSL methods from three perspectives:
data
,model
andalgorithm
. There are some details of reading it.
PV-RCNN[1] is a 3D Object Detection framework to integrate
3D voxel CNN
andPointNet-based set abstraction
to learn more discriminative point cloud features. The most contributions in this papar is two-stage strategy including thevoxel-to-keypoint
3D scene encoding and thekeypoint-to-grid
RoI feature abstraction. There are some details of reading and implementing it.
FairMOT[1] is a one-shot tracker to fuse object detection and re-identification in a single network. The most contributions in this papar are
anchor-free
Re-ID feture extraction, multi-layerfeature aggregation
andlower-dimensional
re-ID fetures. There are some details of reading and implementing it.
Update your browser to view this website correctly. Update my browser now