MOT17-01-DPM
Benchmark:
MOT17 |
Short name:
RGCN_T
Detector:
Public
Description:
we present a unified graph optimization framework to solve the data as- sociation problem in multiple object tracking. The proposed framework build graphs from detection nodes and formulate the graph optimization to a learnable link prediction problem. Specifically, we first use a relational graph convolution net- work (R-GCN) to learn features of both detection nodes and their linked edges. To exploit various edge information, we then use a message passing network (MPN) to aggregate dif- ferent types of edge representations and propagate them on the graph iteratively. Finally, we build an end-to-end learn- able link prediction model by using the leaned edge features to predict if two nodes should be linked. Experimental re- sults on three benchmark datasets demonstrate the effective- ness of the proposed framework, outperforming state-of-the- art methods in multi-object tracking.
Reference:
Last submitted:
October 02, 2020 (6 months ago)
Published:
October 12, 2020 at 08:40:10 CET
Submissions:
3
Project page / code:
n/a
Open source:
No
Hardware:
3 GHZ
Runtime:
59.2 Hz
Benchmark performance:
Sequence | MOTA | IDF1 | HOTA | MOTP | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag |
MOT17 | 63.9 | 66.1 | 53.0 | 79.4 | 795 (33.8) | 655 (27.8) | 22,565 | 179,568 | 68.2 | 94.5 | 54.2 | 52.0 | 60.9 | 73.4 | 55.7 | 77.2 | 82.1 | 1.3 | 1,774 (26.0) | 4,182 (61.3) |
Detailed performance:
Sequence | MOTA | IDF1 | HOTA | MOTP | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag |
MOT17-01-DPM | 50.3 | 63.5 | 49.4 | 76.9 | 8 | 11 | 52 | 3,154 | 51.1 | 98.4 | 64.1 | 38.1 | 70.7 | 76.5 | 39.7 | 76.5 | 80.2 | 0.1 | 2 | 13 |
MOT17-01-FRCNN | 58.1 | 59.0 | 48.5 | 81.5 | 10 | 5 | 383 | 2,289 | 64.5 | 91.6 | 48.2 | 49.2 | 53.8 | 75.5 | 53.7 | 76.2 | 83.6 | 0.9 | 31 | 108 |
MOT17-01-SDP | 49.1 | 59.0 | 45.8 | 76.2 | 9 | 10 | 324 | 2,953 | 54.2 | 91.5 | 53.5 | 39.3 | 61.5 | 70.8 | 42.4 | 71.6 | 79.7 | 0.7 | 6 | 18 |
MOT17-03-DPM | 89.3 | 82.1 | 68.3 | 82.5 | 127 | 0 | 3,221 | 7,766 | 92.6 | 96.8 | 63.6 | 73.5 | 70.0 | 77.6 | 78.4 | 81.9 | 84.6 | 2.1 | 203 | 719 |
MOT17-03-FRCNN | 70.1 | 69.1 | 53.9 | 78.4 | 62 | 17 | 1,949 | 29,297 | 72.0 | 97.5 | 53.3 | 54.8 | 58.2 | 76.3 | 57.8 | 78.3 | 81.4 | 1.3 | 96 | 176 |
MOT17-03-SDP | 75.0 | 72.1 | 56.4 | 77.8 | 80 | 15 | 3,147 | 22,947 | 78.1 | 96.3 | 54.5 | 58.7 | 60.2 | 73.6 | 62.6 | 77.2 | 80.9 | 2.1 | 119 | 232 |
MOT17-06-DPM | 62.9 | 65.5 | 52.2 | 80.7 | 76 | 48 | 289 | 3,934 | 66.6 | 96.4 | 52.5 | 52.0 | 58.1 | 76.6 | 54.9 | 79.6 | 83.2 | 0.2 | 151 | 271 |
MOT17-06-FRCNN | 57.0 | 58.0 | 47.5 | 78.9 | 85 | 62 | 1,432 | 3,581 | 69.6 | 85.1 | 45.4 | 50.0 | 68.7 | 53.3 | 57.3 | 70.0 | 81.3 | 1.2 | 56 | 121 |
MOT17-06-SDP | 57.7 | 59.0 | 47.8 | 78.9 | 95 | 64 | 1,468 | 3,467 | 70.6 | 85.0 | 45.2 | 50.7 | 70.4 | 52.6 | 58.1 | 70.0 | 81.3 | 1.2 | 49 | 123 |
MOT17-07-DPM | 45.3 | 50.7 | 39.6 | 78.0 | 9 | 17 | 604 | 8,575 | 49.2 | 93.2 | 41.7 | 37.9 | 44.8 | 71.1 | 40.0 | 75.7 | 80.8 | 1.2 | 62 | 117 |
MOT17-07-FRCNN | 64.5 | 64.2 | 50.3 | 80.2 | 22 | 3 | 1,050 | 4,832 | 71.4 | 92.0 | 47.6 | 53.3 | 51.2 | 74.0 | 58.5 | 75.4 | 82.6 | 2.1 | 122 | 426 |
MOT17-07-SDP | 47.4 | 52.0 | 40.8 | 77.4 | 11 | 14 | 979 | 7,846 | 53.6 | 90.2 | 41.6 | 40.3 | 46.1 | 67.6 | 43.4 | 73.1 | 80.2 | 2.0 | 69 | 148 |
MOT17-08-DPM | 31.9 | 41.9 | 37.9 | 81.4 | 16 | 38 | 663 | 13,669 | 35.3 | 91.8 | 50.6 | 28.4 | 59.3 | 67.2 | 29.8 | 77.4 | 83.4 | 1.1 | 46 | 56 |
MOT17-08-FRCNN | 38.0 | 40.5 | 34.9 | 81.1 | 18 | 28 | 326 | 12,604 | 40.3 | 96.3 | 38.1 | 32.4 | 42.3 | 72.0 | 33.5 | 79.9 | 83.1 | 0.5 | 157 | 399 |
MOT17-08-SDP | 33.5 | 42.1 | 37.5 | 80.9 | 18 | 38 | 687 | 13,328 | 36.9 | 91.9 | 47.6 | 29.6 | 57.7 | 65.2 | 31.0 | 77.3 | 83.0 | 1.1 | 43 | 53 |
MOT17-12-DPM | 46.5 | 56.4 | 46.8 | 81.6 | 20 | 41 | 367 | 4,257 | 50.9 | 92.3 | 54.6 | 40.2 | 62.1 | 71.7 | 42.8 | 77.7 | 83.5 | 0.4 | 14 | 28 |
MOT17-12-FRCNN | 56.7 | 68.6 | 52.7 | 80.1 | 27 | 20 | 594 | 3,135 | 63.8 | 90.3 | 58.5 | 47.8 | 63.6 | 77.1 | 52.4 | 74.2 | 82.7 | 0.7 | 24 | 178 |
MOT17-12-SDP | 47.0 | 55.9 | 46.4 | 81.2 | 19 | 43 | 372 | 4,207 | 51.5 | 92.3 | 53.3 | 40.4 | 62.3 | 69.2 | 43.2 | 77.4 | 83.5 | 0.4 | 14 | 28 |
MOT17-14-DPM | 49.5 | 62.3 | 44.0 | 74.7 | 43 | 45 | 1,803 | 7,226 | 60.9 | 86.2 | 47.3 | 41.5 | 51.8 | 70.6 | 46.8 | 66.2 | 78.6 | 2.4 | 300 | 572 |
MOT17-14-FRCNN | 34.6 | 46.7 | 34.7 | 75.3 | 19 | 71 | 1,399 | 10,589 | 42.7 | 84.9 | 39.6 | 30.6 | 46.8 | 60.9 | 33.5 | 66.6 | 78.4 | 1.9 | 97 | 183 |
MOT17-14-SDP | 37.9 | 48.3 | 36.0 | 75.4 | 21 | 65 | 1,456 | 9,912 | 46.4 | 85.5 | 39.2 | 33.3 | 46.1 | 60.4 | 36.5 | 67.3 | 78.5 | 1.9 | 113 | 213 |
Raw data: