Object Detection on COCO
58.7AP (Box)MViTv2-L (SoftNMS, MS)
Evaluation Results
| Method | Links | ||||
|---|---|---|---|---|---|
| MViTv2-L (SoftNMS, MS)Backbone=MViTv2-L, Pre-training=IN-21K, Training schedule=50 epochs, large-scale jittering, Inference strategy=SoftNMS and multiscale testing, Params=270 M2021.12 | 58.7 | — | 76.7 | 64.3 | |
| MViTv2-H (IN-21K, LSJ)Backbone=MViTv2-H, Pre-training=IN-21K, Training schedule=50 epochs, large-scale jittering, FLOPs=3084 G, Params=718 M2021.12 | 56.1 | — | 74.6 | 61 | |
| MViTv2-L (IN-21K, LSJ)Backbone=MViTv2-L, Pre-training=IN-21K, Training schedule=50 epochs, large-scale jittering, FLOPs=1519 G, Params=270 M2021.12 | 55.8 | — | 74.3 | 60.9 | |
| EVT-LFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=157, FLOPs (G)=10292026.04 | 55.8 | — | 74.3 | 60.4 | |
| EVT-BFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=114, FLOPs (G)=8492026.04 | 55.5 | — | 74 | 60.2 | |
| MViTv2-B (IN-21K)Backbone=MViTv2-B, Pre-training=IN-21K, FLOPs=814 G, Params=103 M2021.12 | 54.9 | — | 73.8 | 59.8 | |
| CAEBackbone=ViT-L, #Epochs=1600, Pre-training Supervision=Self-supervised, Framework=Mask R-CNN, Schedule=1x2022.02 | 54.6 | — | 75.2 | 59.9 | |
| CAE*Backbone=ViT-L, #Epochs=1600, Pre-training Supervision=Self-supervised, Framework=Mask R-CNN, Schedule=1x2022.02 | 54.5 | — | 75.2 | 60.1 | |
| RMT-BFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=111, FLOPs (G)=8522026.04 | 54.5 | — | 72.8 | 59 | |
| SimMIMBackbone=SwinV2-H2021.11 | 54.4 | — | — | — | |
| MViTv2-LBackbone=MViTv2-L, FLOPs=1519 G, Params=270 M2021.12 | 54.3 | — | 73.1 | 59.1 | |
| MViTv2-BBackbone=MViTv2-B, FLOPs=814 G, Params=103 M2021.12 | 54.1 | — | 72.9 | 58.5 | |
| MAEBackbone=ViT-L, #Epochs=1600, Pre-training Supervision=Self-supervised, Framework=Mask R-CNN, Schedule=1x2022.02 | 54 | — | 74.3 | 59.5 | |
| OverLoCK-BFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=154, FLOPs (G)=10082026.04 | 53.9 | — | — | — | |
| CSWin-BFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=135, FLOPs (G)=10042026.04 | 53.9 | — | 72.6 | 58.5 | |
| SimMIMBackbone=Swin-L2021.11 | 53.8 | — | — | — | |
| EVT-SFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=83, FLOPs (G)=7412026.04 | 53.8 | — | 72.4 | 58.4 | |
| UniFormer-BFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=107, FLOPs (G)=8782026.04 | 53.8 | — | 72.8 | 58.5 | |
| EVT-LFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=119, FLOPs (G)=5502026.04 | 53.6 | — | 74.1 | 58.7 | |
| OverLoCK-SFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=114, FLOPs (G)=8572026.04 | 53.6 | — | — | — | |
| EVT-BFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=76, FLOPs (G)=3712026.04 | 53.3 | — | 73.9 | 58.4 | |
| MViTv2-SBackbone=MViTv2-S, FLOPs=748 G, Params=87 M2021.12 | 53.2 | — | 72.4 | 58 | |
| RMT-SFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=83, FLOPs (G)=7412026.04 | 53.2 | — | 72 | 57.8 | |
| UniRepLKNet-SFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=113, FLOPs (G)=8352026.04 | 53 | — | — | — | |
| GC ViT-BFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=146, FLOPs (G)=10182026.04 | 52.9 | — | 71.7 | 57.8 | |
| DAT-SFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=107, FLOPs (G)=8572026.04 | 52.7 | — | 71.7 | 57.2 | |
| CSWin-TFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=80, FLOPs (G)=7572026.04 | 52.5 | — | 71.5 | 57.1 | |
| SimMIMBackbone=Swin-B2021.11 | 52.3 | — | — | — | |
| MViTv2-TBackbone=MViTv2-T, FLOPs=701 G, Params=76 M2021.12 | 52.2 | — | 71.1 | 56.6 | |
| RMT-BFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=73, FLOPs (G)=3732026.04 | 52.2 | — | 72.9 | 57 | |
| UniFormer-SFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=79, FLOPs (G)=7472026.04 | 52.1 | — | 71.1 | 56.6 | |
| Full-precisionNetwork=Swin-S + Cascade Mask R-CNN, #Bits=32/32, Size=427.82024.11 | 51.9 | — | — | — | |
| Full-precisionNetwork=Swin-B + Cascade Mask R-CNN, #Bits=32/32, Size=579.92024.11 | 51.9 | — | — | — | |
| Swin-BBackbone=Swin-B, FLOPs=982 G, Params=145 M2021.12 | 51.9 | — | 70.9 | 56.5 | |
| SMT-SFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=78, FLOPs (G)=7442026.04 | 51.9 | — | 70.5 | 56.3 | |
| Swin-SFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=107, FLOPs (G)=8382026.04 | 51.9 | — | 70.7 | 56.3 | |
| NAT-SFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=108, FLOPs (G)=8092026.04 | 51.9 | — | 70.4 | 56.2 | |
| Swin-BFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=145, FLOPs (G)=9822026.04 | 51.9 | — | 70.5 | 56.4 | |
| RepQ-ViT + QwTNetwork=Swin-B + Cascade Mask R-CNN, #Bits=6/6, Size=126.12024.11 | 51.8 | — | — | — | |
| Swin-SBackbone=Swin-S, FLOPs=838 G, Params=107 M2021.12 | 51.8 | — | 70.4 | 56.3 | |
| UniRepLKNet-TFramework=Cascade Mask R-CNN, Schedule=3x+MS, Params (M)=89, FLOPs (G)=7492026.04 | 51.8 | — | — | — | |
| RepQ-ViT + QwTNetwork=Swin-S + Cascade Mask R-CNN, #Bits=6/6, Size=91.32024.11 | 51.7 | — | — | — | |
| EVT-SFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=45, FLOPs (G)=2622026.04 | 51.6 | — | 72.4 | 56.6 | |
| RepQ-ViTNetwork=Swin-B + Cascade Mask R-CNN, #Bits=6/6, Size=112.12024.11 | 51.5 | — | — | — | |
| RepQ-ViTNetwork=Swin-S + Cascade Mask R-CNN, #Bits=6/6, Size=83.42024.11 | 51.4 | — | — | — | |
| iBOTPretrain Epochs=1600, Backbone=ViT-B/162024.10 | 51.2 | — | — | — | |
| SupervisedBackbone=Swin-L2021.11 | 50.9 | — | — | — | |
| C-JEPAPretrain Epochs=600, Backbone=ViT-B/162024.10 | 50.7 | — | — | — | |
| RMT-SFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=46, FLOPs (G)=2622026.04 | 50.7 | — | 71.9 | 55.6 | |
| Swin-TBackbone=Swin-T, FLOPs=745 G, Params=86 M2021.12 | 50.5 | — | 69.3 | 54.9 | |
| MILA-SFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=63, FLOPs (G)=3192026.04 | 50.5 | — | 71.8 | 55.2 | |
| MAEPretrain Epochs=1600, Backbone=ViT-B/162024.10 | 50.3 | — | — | — | |
| InternImage-BFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=115, FLOPs (G)=5012026.04 | 50.3 | — | 71.4 | 55.3 | |
| SupervisedBackbone=Swin-B2021.11 | 50.2 | — | — | — | |
| SupervisedBackbone=SwinV2-H2021.11 | 50.2 | — | — | — | |
| CAEBackbone=ViT-B, #Epochs=1600, Pre-training Supervision=Self-supervised, Framework=Mask R-CNN, Schedule=1x2022.02 | 50.2 | — | 71 | 54.9 | |
| DINOPretrain Epochs=1600, Backbone=ViT-B/162024.10 | 50.1 | — | — | — | |
| RepQ-ViT + QwTNetwork=Swin-B + Cascade Mask R-CNN, #Bits=4/4, Size=90.12024.11 | 50 | — | — | — | |
| CAE*Backbone=ViT-B, #Epochs=1600, Pre-training Supervision=Self-supervised, Framework=Mask R-CNN, Schedule=1x2022.02 | 50 | — | 70.9 | 54.8 | |
| CSWin-SFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=54, FLOPs (G)=3422026.04 | 50 | — | 71.3 | 54.7 | |
| RepQ-ViT + QwTNetwork=Swin-S + Cascade Mask R-CNN, #Bits=4/4, Size=64.82024.11 | 49.9 | — | — | — | |
| I-JEPAPretrain Epochs=600, Backbone=ViT-B/162024.10 | 49.9 | — | — | — | |
| CAE*Backbone=ViT-B, #Epochs=800, Pre-training Supervision=Self-supervised, Framework=Mask R-CNN, Schedule=1x2022.02 | 49.8 | — | 70.7 | 54.6 | |
| BEiTPretrain Epochs=800, Backbone=ViT-B/162024.10 | 49.8 | — | — | — | |
| InternImage-SFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=69, FLOPs (G)=3402026.04 | 49.7 | — | 71.1 | 54.5 | |
| ViT-Adapter-BFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=120, FLOPs (G)=8322026.04 | 49.6 | — | 70.6 | 54 | |
| RepQ-ViTNetwork=Swin-S + Cascade Mask R-CNN, #Bits=4/4, Size=56.92024.11 | 49.3 | — | — | — | |
| RepQ-ViTNetwork=Swin-B + Cascade Mask R-CNN, #Bits=4/4, Size=76.12024.11 | 49.3 | — | — | — | |
| InternImage-TFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=49, FLOPs (G)=2702026.04 | 49.1 | — | 70.4 | 54.1 | |
| SMT-SFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=40, FLOPs (G)=2652026.04 | 49 | — | 70.1 | 53.4 | |
| CSWin-TFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=42, FLOPs (G)=2792026.04 | 49 | — | 70.7 | 53.7 | |
| DetCon_BData=IN-1M, Params=250 M2021.03 | 48.9 | — | — | — | |
| Cascade RCNNBackbone=ViTAE-S-Stage, Lr Schd=1x, Params (M)=752021.06 | 48.9 | — | — | — | |
| VSSD-TFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=44, FLOPs (G)=2652026.04 | 48.8 | — | 70.4 | 53.4 | |
| MILA-TFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=44, FLOPs (G)=2552026.04 | 48.8 | — | 71 | 53.6 | |
| Swin-BFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=107, FLOPs (G)=4962026.04 | 48.6 | — | 70 | 53.4 | |
| Full-precisionNetwork=Swin-S + Mask R-CNN, #Bits=32/32, Size=276.52024.11 | 48.5 | — | — | — | |
| SEERData=IG-1B, Params=693 M2021.03 | 48.5 | — | — | — | |
| Swin-SFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=69, FLOPs (G)=3592026.04 | 48.5 | — | 70.2 | 53.5 | |
| MAEBackbone=ViT-B, #Epochs=1600, Pre-training Supervision=Self-supervised, Framework=Mask R-CNN, Schedule=1x2022.02 | 48.4 | — | 69.4 | 53.1 | |
| CAE*Backbone=ViT-B, #Epochs=300, Pre-training Supervision=Self-supervised, Framework=Mask R-CNN, Schedule=1x2022.02 | 48.4 | — | 69.2 | 52.9 | |
| MPViT-SFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=43, FLOPs (G)=2682026.04 | 48.4 | — | 70.5 | 52.6 | |
| X101-64Backbone=ResNeXt-101-64x4d, FLOPs=972 G, Params=140 M2021.12 | 48.3 | — | 66.4 | 52.3 | |
| iBOTBackbone=ViT-B, #Epochs=1600+, Pre-training Supervision=Self-supervised, Framework=Mask R-CNN, Schedule=1x2022.02 | 48.2 | — | 69.7 | 52.8 | |
| Cascade RCNNBackbone=Swin-T, Lr Schd=1x, Params (M)=862021.06 | 48.1 | — | — | — | |
| X101-32Backbone=ResNeXt-101-32x4d, FLOPs=819 G, Params=101 M2021.12 | 48.1 | — | 66.5 | 52.4 | |
| RepQ-ViT + QwTNetwork=Swin-S + Mask R-CNN, #Bits=6/6, Size=61.22024.11 | 48 | — | — | — | |
| ConvNeXt-SFramework=Mask R-CNN, Schedule=3x+MS, Params (M)=70, FLOPs (G)=3482026.04 | 47.9 | — | 70 | 52.7 | |
| RepQ-ViTNetwork=Swin-S + Mask R-CNN, #Bits=6/6, Size=53.32024.11 | 47.6 | — | — | — | |
| DetCon_BBackbone=ResNet-200, Fine-tune schedule=2x, Pre-trained on=ImageNet2021.03 | 47.2 | — | — | — | |
| DetCon_BBackbone=ResNet-200, Fine-tune schedule=1x, Pre-trained on=ImageNet2021.03 | 47.1 | — | — | — | |
| DeiTBackbone=ViT-B, #Epochs=300, Pre-training Supervision=Supervised, Framework=Mask R-CNN, Schedule=1x2022.02 | 46.9 | — | 68.9 | 51 | |
| DINOBackbone=ViT-B, #Epochs=1600+, Pre-training Supervision=Self-supervised, Framework=Mask R-CNN, Schedule=1x2022.02 | 46.8 | — | 68.6 | 50.9 | |
| Res50Backbone=ResNet-50, FLOPs=739 G, Params=82 M2021.12 | 46.3 | — | 64.3 | 50.5 | |
| BYOLBackbone=ResNet-200, Fine-tune schedule=2x, Pre-trained on=ImageNet2021.03 | 45.9 | — | — | — | |
| SupervisedData=IN-1M, Params=250 M2021.03 | 45.9 | — | — | — | |
| BYOLBackbone=ResNet-200, Fine-tune schedule=1x, Pre-trained on=ImageNet2021.03 | 45.6 | — | — | — | |
| MoCo v3Backbone=ViT-B, #Epochs=600+, Pre-training Supervision=Self-supervised, Framework=Mask R-CNN, Schedule=1x2022.02 | 45.5 | — | 67.1 | 49.4 | |
| MAEBackbone=ViT-B, #Epochs=300, Pre-training Supervision=Self-supervised, Framework=Mask R-CNN, Schedule=1x2022.02 | 45.4 | — | 66.4 | 49.6 | |
| SimCLRBackbone=ResNet-200, Fine-tune schedule=2x, Pre-trained on=ImageNet2021.03 | 45.3 | — | — | — |