Face Detection on FDDB
92Recall @ 1% FPPITiny-YOLO
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| Tiny-YOLOmodel size (MB)=63.002019.11 | 92 | — | — | |
| Tiny-YOLO#FLOPS (million)=24,407, Model size(KB)=62,5162019.11 | 92 | — | — | |
| Proposed (RSA+LRN)Scale-forecast=tiny ResNet-18, RSA=4-layer FCN, LRN=tiny ResNet-18, Opts. (VGA input)=95.67M to 1.5G2017.07 | 91.92 | — | — | |
| RPN_sStructure=single anchor, Opts. (VGA input)=1.72G, Backbone=ResNet-182017.07 | 90.61 | — | — | |
| DupNet-L+PACT#FLOPS (million)=95.7, Model size(KB)=45.4, clipping thresholds=PACT2019.11 | 90.6 | — | — | |
| Tinier-YOLO#FLOPS (million)=3,213, Model size(KB)=7,7072019.11 | 90.2 | — | — | |
| Tinier-YOLOmodel size (MB)=7.892019.11 | 90 | — | — | |
| IFQ-Tiny-YOLOmodel size (MB)=1.97, k=22019.11 | 89 | — | — | |
| DupNet-L#FLOPS (million)=95.7, Model size(KB)=45.42019.11 | 88.4 | — | — | |
| DupNet+PACT#FLOPS (million)=62.6, Model size(KB)=36.9, clipping thresholds=PACT2019.11 | 88 | — | — | |
| RPN_mStructure=multi anchors, Opts. (VGA input)=1.31G, Backbone=ResNet-182017.07 | 86.89 | — | — | |
| DupNet#FLOPS (million)=62.6, Model size(KB)=36.92019.11 | 85.9 | — | — | |
| IFQ-Tinier-YOLOmodel size (MB)=0.25, k=22019.11 | 84 | — | — | |
| IFQ-Tinier-YOLO#FLOPS (million)=107.9, Model size(KB)=240.92019.11 | 83.5 | — | — | |
| ASFD2021.05 | — | — | 99.11 | |
| Condensation-NetAlpha=2, Pooling Type=Max Pooling, Network Precision=Quantized2021.04 | — | 91.82 | — | |
| Condensation-NetAlpha=2, Pooling Type=Max Pooling, Network Precision=Full-Precision2021.04 | — | 93.86 | — | |
| Condensation-NetAlpha=2, Pooling Type=Average Pooling, Network Precision=Quantized2021.04 | — | 91.13 | — | |
| Condensation-NetAlpha=2, Pooling Type=Average Pooling, Network Precision=Full-Precision2021.04 | — | 93.69 | — | |
| Condensation-NetAlpha=4, Pooling Type=Max Pooling, Network Precision=Quantized2021.04 | — | 90.25 | — | |
| Condensation-NetAlpha=4, Pooling Type=Max Pooling, Network Precision=Full-Precision2021.04 | — | 93.61 | — | |
| Condensation-NetAlpha=4, Pooling Type=Average Pooling, Network Precision=Quantized2021.04 | — | 90.74 | — | |
| Condensation-NetAlpha=4, Pooling Type=Average Pooling, Network Precision=Full-Precision2021.04 | — | 93.56 | — | |
| FaceBoxes2021.05 | — | — | 95.98 | |
| PyramidBox2021.05 | — | — | 98.69 | |
| RefineFace2021.05 | — | — | 99.11 | |
| Tiny-YOLOv2Network Precision=Quantized2021.04 | — | 89.87 | — | |
| Tiny-YOLOv2Network Precision=Full-Precision2021.04 | — | 92.28 | — | |
| YOLOv5lvariant=large2021.05 | — | — | 98.67 | |
| YOLOv5l6variant=large-62021.05 | — | — | 98.8 | |
| YOLOv5mvariant=medium2021.05 | — | — | 98.49 | |
| YOLOv5svariant=small2021.05 | — | — | 98.43 |