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Models/DeformConv-R-FCN (Aligned-Inception-ResNet)

DeformConv-R-FCN (Aligned-Inception-ResNet)

Reported on 25 benchmarks across 5 tasks · 1 paper · 22 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology20 results

3DonCOCO test-dev
APS· 2017-03-17
19.4
best: 48.6 (Focal-Stable-DINO (Focal-Huge, no TTA))
SOTA
Deformable Convolutional Networks arXiv:1703.06211
3DonCOCO test-dev
box mAP· 2017-03-17
37.5
best: 66 (Co-DETR)
SOTA
Deformable Convolutional Networks arXiv:1703.06211
2D ClassificationonCOCO test-dev
AP50· 2017-03-17
58
best: 82.1 (Plain-DETR (Swin-L))
SOTA
Deformable Convolutional Networks arXiv:1703.06211
2D ClassificationonCOCO test-dev
APL· 2017-03-17
52.5
best: 78 (Focal-Stable-DINO (Focal-Huge, no TTA))
SOTA
Deformable Convolutional Networks arXiv:1703.06211
2D ClassificationonCOCO test-dev
APM· 2017-03-17
40.1
best: 67.7 (EVA)
SOTA
Deformable Convolutional Networks arXiv:1703.06211
2D ClassificationonCOCO test-dev
APS· 2017-03-17
19.4
best: 48.6 (Focal-Stable-DINO (Focal-Huge, no TTA))
SOTA
Deformable Convolutional Networks arXiv:1703.06211
2D ClassificationonCOCO test-dev
box mAP· 2017-03-17
37.5
best: 66 (Co-DETR)
SOTA
Deformable Convolutional Networks arXiv:1703.06211
2D Object DetectiononCOCO test-dev
AP50· 2017-03-17
58
best: 82.1 (Plain-DETR (Swin-L))
SOTA
Deformable Convolutional Networks arXiv:1703.06211
2D Object DetectiononCOCO test-dev
APL· 2017-03-17
52.5
best: 78 (Focal-Stable-DINO (Focal-Huge, no TTA))
SOTA
Deformable Convolutional Networks arXiv:1703.06211
2D Object DetectiononCOCO test-dev
APM· 2017-03-17
40.1
best: 67.7 (EVA)
SOTA
Deformable Convolutional Networks arXiv:1703.06211
2D Object DetectiononCOCO test-dev
APS· 2017-03-17
19.4
best: 48.6 (Focal-Stable-DINO (Focal-Huge, no TTA))
SOTA
Deformable Convolutional Networks arXiv:1703.06211
2D Object DetectiononCOCO test-dev
box mAP· 2017-03-17
37.5
best: 66 (Co-DETR)
SOTA
Deformable Convolutional Networks arXiv:1703.06211
16konCOCO test-dev
AP50· 2017-03-17
58
best: 82.1 (Plain-DETR (Swin-L))
SOTA
Deformable Convolutional Networks arXiv:1703.06211
16konCOCO test-dev
APL· 2017-03-17
52.5
best: 78 (Focal-Stable-DINO (Focal-Huge, no TTA))
SOTA
Deformable Convolutional Networks arXiv:1703.06211
16konCOCO test-dev
APM· 2017-03-17
40.1
best: 67.7 (EVA)
SOTA
Deformable Convolutional Networks arXiv:1703.06211
16konCOCO test-dev
APS· 2017-03-17
19.4
best: 48.6 (Focal-Stable-DINO (Focal-Huge, no TTA))
SOTA
Deformable Convolutional Networks arXiv:1703.06211
16konCOCO test-dev
box mAP· 2017-03-17
37.5
best: 66 (Co-DETR)
SOTA
Deformable Convolutional Networks arXiv:1703.06211
3DonCOCO test-dev
AP50· 2017-03-17
58
best: 95 (ViTPose (ViTAE-G, ensemble))
Deformable Convolutional Networks arXiv:1703.06211
3DonCOCO test-dev
APL· 2017-03-17
52.5
best: 86.5 (PoseBH-H)
Deformable Convolutional Networks arXiv:1703.06211
3DonCOCO test-dev
APM· 2017-03-17
40.1
best: 83.8 (4xRSN-50 (ensemble))
Deformable Convolutional Networks arXiv:1703.06211

Computer Vision5 results

Object DetectiononCOCO test-dev
AP50· 2017-03-17
58
best: 82.1 (Plain-DETR (Swin-L))
SOTA
Deformable Convolutional Networks arXiv:1703.06211
Object DetectiononCOCO test-dev
APL· 2017-03-17
52.5
best: 78 (Focal-Stable-DINO (Focal-Huge, no TTA))
SOTA
Deformable Convolutional Networks arXiv:1703.06211
Object DetectiononCOCO test-dev
APM· 2017-03-17
40.1
best: 67.7 (EVA)
SOTA
Deformable Convolutional Networks arXiv:1703.06211
Object DetectiononCOCO test-dev
APS· 2017-03-17
19.4
best: 48.6 (Focal-Stable-DINO (Focal-Huge, no TTA))
SOTA
Deformable Convolutional Networks arXiv:1703.06211
Object DetectiononCOCO test-dev
box mAP· 2017-03-17
37.5
best: 66 (Co-DETR)
SOTA
Deformable Convolutional Networks arXiv:1703.06211