Opto-Electronic Engineering, Volume. 50, Issue 1, 220180(2023)
Few-shot object detection via online inferential calibration
Figures & Tables(15)
Fig. 9. Detection results under the occlusion conditions in the 10 shot task
Fig. 10. 10 shot task detection results. (a) Detection results of the Faster R-CNN network based on TFA; (b) Detection results of the Faster R-CNN net work using the online inference calibration module; (c) Detection results of the Faster R-CNN network using the online inference calibration module and adding the Attention-FPN network
Table 1. Hierarchical freezing mechanism
View tableView in ArticleTable 1. Hierarchical freezing mechanism
Shot Backbone Regressor Classifer Attention-FPN RPN ROI 1 × √ √ × × × 2 × × × 3 √ × √ 5 √ √ √ 10 √ √ √
Table 2. Experimental settings of the dataset
View tableView in ArticleTable 2. Experimental settings of the dataset
Dataset Shot Number of categories Initial learning rate Batch_size Decay ratio of learning rate Number of attenuation Iterations VOC 1 20 0.001 16 0.1 1 6000 2 0.1 1 7000 3 0.1 2 8000 5 0.5 2 9000 10 0.5 2 13000 COCO 10 80 0.001 16 0.3 1 30000 30 40000
Table 3. Performance analysis and comparison of the few shot object detection algorithm in VOC new class partition sets
View tableView in ArticleTable 3. Performance analysis and comparison of the few shot object detection algorithm in VOC new class partition sets
Method Year Novel Set 1 Novel Set 2 Novel Set 3 1 2 3 5 10 1 2 3 5 10 1 2 3 5 10 LSTD[ 26 ]AAAI 18 8.2 1.0 12.4 29.1 38.5 11.4 3.8 5.0 15.7 31.0 12.6 8.5 15.0 27.3 36.3 MetaDet[ 40 ]ICCV 19 18.9 20.6 30.2 36.8 49.6 21.8 23.1 27.8 31.7 43.0 20.6 23.9 29.4 43.9 44.1 Meta R-CNN[ 15 ]ICCV 19 19.9 25.5 35.0 45.7 51.5 10.4 19.4 29.6 34.8 45.4 14.3 18.2 27.5 41.2 48.1 RepMet[ 28 ]CVPR 19 26.1 32.9 34.4 38.6 41.3 17.2 22.1 23.4 28.3 35.8 27.5 31.1 31.5 34.4 37.2 FSRW[ 37 ]ICCV 19 14.8 15.5 26.7 33.9 47.2 15.7 15.3 22.7 30.1 40.5 21.3 25.6 28.4 42.8 45.9 FSDetView[ 42 ]ECCV 20 24.2 35.3 42.2 49.1 57.4 21.6 24.6 31.9 37.0 45.7 21.2 30.0 37.2 43.8 49.6 TFA w/cos[ 44 ]ICML 20 39.8 36.1 44.7 55.7 56.0 23.5 26.9 34.1 35.1 39.1 30.8 34.8 42.8 49.5 49.8 MPSR[ 51 ]ECCV 20 41.7 - 51.4 55.2 61.8 24.4 - 39.2 39.9 47.8 35.6 - 42.3 48.0 49.7 TFA w/cos+Halluc[ 18 ]CVPR 21 45.1 44.0 44.7 55.0 55.9 23.2 27.5 35.1 34.9 39.0 30.5 35.1 41.4 49.0 49.3 TIP[ 41 ]CVPR 21 27.7 36.5 43.3 50.2 59.6 22.7 30.1 33.8 40.9 46.9 21.7 30.6 38.1 44.5 50.9 FSCE[ 25 ]CVPR 21 44.2 43.8 51.4 61.9 63.4 27.3 29.5 43.5 44.2 50.2 37.2 41.9 47.5 54.6 58.5 Retentive R-CNN[ 45 ]CVPR 21 42.4 45.8 45.9 53.7 56.1 21.7 27.8 35.2 37.0 40.3 30.2 37.6 43.0 49.7 50.1 Meta-DETR[ 38 ]IEEE 22 35.1 49.0 53.2 57.4 62.0 27.9 32.3 38.4 43.2 51.8 34.9 41.8 47.1 54.1 58.2 AGCM[ 33 ]IEEE 22 40.3 - - 58.5 59.9 27.5 - - 49.3 50.6 42.1 - - 54.2 58.2 FSOIC(Ours) 46.6 53.4 56.6 62.0 64.5 25.7 30.5 43.8 45.9 53.3 42.4 44.9 49.5 56.6 58.8
Table 4. Performance analysis and comparison of few shot object detection algorithms in the COCO datasets
View tableView in ArticleTable 4. Performance analysis and comparison of few shot object detection algorithms in the COCO datasets
Method Year Novel AP 10 30 LSTD [ 26 ]AAAI 18 3.2 6.7 FSRW [ 37 ]ICCV 19 5.6 9.1 MPSR[ 51 ]ECCV 20 9.8 14.1 TFA w/cos [ 44 ]ICML 20 10.0 13.7 Retentive R-CNN [ 45 ]CVPR 21 10.5 13.8 FSCE[ 25 ]CVPR 21 11.9 16.4 FSOIC(Ours) 12.7 16.7
Table 5. Comparison of the ablation experimental performance
View tableView in ArticleTable 5. Comparison of the ablation experimental performance
Method FPN+4*ROI Finetune RPN Online calibration Attention of channel Novel Set1 1 3 10 TFA w/cos[ 44 ]- - - - 39.8 44.7 56.0 FSOIC(Ours) √ × × × 43.6 52.2 62.5 FSOIC(Ours) √ √ × × 44.1 53.0 63.2 FSOIC(Ours) √ √ √ × 45.7 54.2 64.2 FSOIC(Ours) √ × √ √ 46.2 54.9 62.8 FSOIC(Ours) √ √ × √ 44.7 54.0 61.7 FSOIC(Ours) √ √ √ √ 46.6 56.6 64.5
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Hao Peng, Wanqi Wang, Long Chen, Xianrong Peng, Jianlin Zhang, Zhiyong Xu, Yuxing Wei, Meihui Li. Few-shot object detection via online inferential calibration[J]. Opto-Electronic Engineering, 2023, 50(1): 220180
Paper Information
Category: Article
Received: Jul. 27, 2022
Accepted: Dec. 29, 2022
Published Online: Feb. 27, 2023
The Author Email: Peng Xianrong (peng_xr@ioe.ac.cn)
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