I found that the core of generating virtual points in the article lies in using 2D masks to achieve random sampling enhancement for 3D point cloud in a simple and effective way. At the same time, I have observed some issues in my experiments. I found that objects in Lidar modal data such as cars and pedestrians seem to be more sensitive to edge contours, enhancing the continuity and integrity of the contours, making the shape of Lidar more prominent.
This seems to bring greater improvement for 3D detection. In the future, I plan to delve deeper into researching and transforming the ideas from your paper into my own. Thank you for your work!
I found that the core of generating virtual points in the article lies in using 2D masks to achieve random sampling enhancement for 3D point cloud in a simple and effective way. At the same time, I have observed some issues in my experiments. I found that objects in Lidar modal data such as cars and pedestrians seem to be more sensitive to edge contours, enhancing the continuity and integrity of the contours, making the shape of Lidar more prominent.
This seems to bring greater improvement for 3D detection. In the future, I plan to delve deeper into researching and transforming the ideas from your paper into my own. Thank you for your work!