Fig. 1. Algorithm frame diagram

Fig. 2. Mask prediction module

Fig. 3. Prediction module

Fig. 4. Point cloud projection

Fig. 5. Calibration board effect

Fig. 6. Mask projection

Fig. 7. Input sequence RGB and mask data into the model. (a) Original sequence RGB data; (b) Corresponding sequence mask data

Fig. 8. Loss function curve. (a) Four definitions of loss; (b) Total algorithm loss

Fig. 9. PR curve comparison

Fig. 10. The accuracy of the three algorithms for different distance, occlusion, luminosity and ambiguity

Fig. 11. Performance of multiple target tracking algorithms on MOT

Fig. 12. Effect of Apollo dataset test

Fig. 13. Effect of KITTI dataset test

Fig. 14. Effect of BDD100K dataset test

Fig. 15. Effect of point cloud projection

Fig. 16. Experimental platform

Fig. 17. Effect of actual road experiment