Details for method 'QueryInst-Parallel Completion'
Method overview
| name |
QueryInst-Parallel Completion |
| challenge |
instance-level semantic labeling |
| details |
We propose a novel feature complete network framework queryinst parallel completion. First, the global context module is introduced into the backbone network to obtain instance information. Then, parallel semantic branch and parallel global branch are proposed to extract the semantic information and global information of feature layer, so as to complete the ROI features. In addition, we also propose a feature transfer structure, which explicitly increases the connection between detection and segmentation branches, changes the gradient back-propagation path, and indirectly complements the ROI features. |
| publication |
Hai Wang ;Shilin Zhu ;PuPu ;Meng; Le; Apple; Rong
|
| project page / code |
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| used Cityscapes data |
fine annotations |
| used external data |
CoCo |
| runtime |
n/a |
| subsampling |
no |
| submission date |
June, 2022 |
| previous submissions |
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Average results
| Metric |
Value |
| AP | 35.3755 |
| AP50% | 60.8685 |
| AP100m | 48.1494 |
| AP50m | 50.8495 |
Class results
| Class |
AP | AP50% | AP100m | AP50m |
| person | 41.4128 | 72.8727 | 58.3291 | 58.4702 |
| rider | 31.4676 | 67.6387 | 43.6556 | 43.9216 |
| car | 58.4295 | 83.0294 | 76.765 | 79.2953 |
| truck | 29.1902 | 41.1777 | 38.751 | 43.4567 |
| bus | 43.9733 | 61.8997 | 61.6092 | 68.6619 |
| train | 31.6175 | 53.4349 | 43.5638 | 49.8545 |
| motorcycle | 24.9731 | 53.272 | 31.8189 | 32.5246 |
| bicycle | 21.9403 | 53.6231 | 30.7027 | 30.6113 |
Links
Download results as .csv file
Benchmark page
