During this week, I changed the 3D convolution neural network part, and added the resnet work into it. I tried to train the model again from the first epoch, not using the pretrained pth files.
Also, I figure out the problem that the computational quantity of 3D CNN. In … Continue Reading ››
PV-RCNN is a 3D detection paper that I am reading. This paper concentrated the 2 points into one framework: voxel CNN, and key-point refine, which is also a two-stage framework.
I used many time to learn the detailed deep learning strategy, including the classic learning structure: resnet and inception. I want to do some structure improvement in the traditional deep learning frameworks. But until now, I have no ideas when I face yolov4.
Based on the work of ICISIP2021 paper, I felt the detection FPS is not so fast to maintain the real-time requirement. Actually, My 3D_Detection_YOLOv4 work could maintain 20-30 FPS on 2060 Super. The safe FPS is better above 30FPS stably. I guess my work last month could get better FPS on other machine.
This month, I put most of my time on C++ programming learning. I am learning a set of courses on the website. The course is divided by 3 parts, I have learnt all the classes except the last parts.
Last week I learned the Pointnet work, then this week I resume to stuty the Pointnet++. The 3D object detection framework PointRCNN used the improved pointnet++ to process the point clouds data. This is a two stage detecting work, and I am studying its program. I tried to run PointRCNN, but not … Continue Reading ››