Infrared Small Target Detection on NUDT-MIRSDT
98.5Probability of Detection (Pd)DeepPro
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| DeepProProcessing Type=MF, Method Category=Deep-Learning, #Params (M)=0.197, FPS=184.552025.06 | 98.5 | 0.72 | 0.9973 | |
| Res-U+DTUMProcessing Type=MF, Method Category=Deep-Learning, #Params (M)=1.193, FPS=62.652025.06 | 97.46 | 3 | 0.9967 | |
| STDMANetProcessing Type=MF, Method Category=Deep-Learning, #Params (M)=47.518, FPS=18.662025.06 | 96.59 | 3.4 | 0.9908 | |
| DQAlignerProcessing Type=MF, Method Category=Deep-Learning, #Params (M)=2.410, FPS=10.012025.06 | 94.22 | 0.15 | 0.9419 | |
| Res-U+RFRProcessing Type=MF, Method Category=Deep-Learning, #Params (M)=4.096, FPS=102.882025.06 | 93.35 | 1.95 | 0.9657 | |
| SRSTTProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=0.062025.06 | 90.63 | 3.35 | 0.9989 | |
| DNA-NetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=18.787, FPS=29.872025.06 | 67.38 | 15.07 | 0.8843 | |
| ISNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=4.363, FPS=52.252025.06 | 65.99 | 19.25 | 0.9123 | |
| Res-UNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=3.656, FPS=222.852025.06 | 63.27 | 40.83 | 0.9198 | |
| SCTransNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=45.304, FPS=20.072025.06 | 62.81 | 74.2 | 0.932 | |
| UIUNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=202.152, FPS=12.462025.06 | 61.25 | 14.42 | 0.9436 | |
| RPCANetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=2.720, FPS=31.472025.06 | 61.13 | 41.28 | 0.8694 | |
| ILNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=6.322, FPS=36.822025.06 | 57.9 | 34.09 | 0.7572 | |
| 4D-TRProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=0.362025.06 | 55.7 | 3.19 | 0.9946 | |
| AGPCNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=49.442, FPS=24.132025.06 | 55.47 | 85.56 | 0.9443 | |
| ALCNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=3.457, FPS=142.512025.06 | 52.57 | 25.5 | 0.8435 | |
| ACMProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=1.592, FPS=171.312025.06 | 51.53 | 17.52 | 0.9298 | |
| 4DST-BTMDProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=26.092025.06 | 44.77 | 74.95 | 0.8488 | |
| MSHNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=16.262, FPS=69.352025.06 | 36.78 | 41.91 | 0.7966 | |
| 4D-TTProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=10.822025.06 | 30.89 | 3.21 | 0.8287 | |
| IMNN-LWECProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=30.312025.06 | 26.43 | 10.74 | 0.6734 | |
| STRL-LBCMProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=0.872025.06 | 19.03 | 34.05 | 0.5972 | |
| MSLSTIPTProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=0.172025.06 | 18.97 | 15.37 | 0.9404 | |
| NFTDGSTVProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=0.582025.06 | 13.77 | 35.32 | 0.8613 |