Infrared Small Target Detection on NUDT-MIRSDT HiNo
59.17PdDeepPro
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| DeepProProcessing Type=MF, Method Category=Deep-Learning, #Params (M)=0.197, FPS=184.552025.06 | 59.17 | 1.76 | 0.9638 | |
| Res-U+RFRProcessing Type=MF, Method Category=Deep-Learning, #Params (M)=4.096, FPS=102.882025.06 | 55.64 | 111.23 | 0.7839 | |
| STDMANetProcessing Type=MF, Method Category=Deep-Learning, #Params (M)=47.518, FPS=18.662025.06 | 51.65 | 1.95 | 0.8766 | |
| DNA-NetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=18.787, FPS=29.872025.06 | 49.16 | 60.98 | 0.9373 | |
| Res-U+DTUMProcessing Type=MF, Method Category=Deep-Learning, #Params (M)=1.193, FPS=62.652025.06 | 43.9 | 4.86 | 0.9413 | |
| UIUNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=202.152, FPS=12.462025.06 | 43.67 | 28.87 | 0.9246 | |
| AGPCNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=49.442, FPS=24.132025.06 | 42.452 | 13,655.2 | 0.7348 | |
| ALCNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=3.457, FPS=142.512025.06 | 36.09 | 91.99 | 0.9326 | |
| Res-UNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=3.656, FPS=222.852025.06 | 35.51 | 22.55 | 0.9391 | |
| ILNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=6.322, FPS=36.822025.06 | 34.11 | 56.53 | 0.6551 | |
| DQAlignerProcessing Type=MF, Method Category=Deep-Learning, #Params (M)=2.410, FPS=10.012025.06 | 33.41 | 2.95 | 0.8022 | |
| ISNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=4.363, FPS=52.252025.06 | 28.4 | 90.17 | 0.9224 | |
| MSHNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=16.262, FPS=69.352025.06 | 21.81 | 44.92 | 0.6748 | |
| RPCANetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=2.720, FPS=31.472025.06 | 21.81 | 198.14 | 0.8786 | |
| SCTransNetProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=45.304, FPS=20.072025.06 | 20.65 | 35.37 | 0.8283 | |
| NFTDGSTVProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=0.582025.06 | 11.56 | 43.16 | 0.9524 | |
| 4D-TTProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=10.822025.06 | 6.94 | 73.18 | 0.5347 | |
| IMNN-LWECProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=30.312025.06 | 4.97 | 83.28 | 0.5394 | |
| 4DST-BTMDProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=26.092025.06 | 4.8 | 77.29 | 0.6651 | |
| 4D-TRProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=0.362025.06 | 4.63 | 120.16 | 0.6633 | |
| SRSTTProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=0.062025.06 | 4.34 | 55.04 | 0.5358 | |
| MSLSTIPTProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=0.172025.06 | 3.93 | 73.76 | 0.9185 | |
| STRL-LBCMProcessing Type=MF, Method Category=Traditional, #Params (M)=-, FPS=0.872025.06 | 2.55 | 77.78 | 0.5238 | |
| ACMProcessing Type=SF, Method Category=Deep-Learning, #Params (M)=1.592, FPS=171.312025.06 | 0 | — | — |