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Models/WCCN

WCCN

Reported on 20 benchmarks across 5 tasks · 1 paper · 19 SOTA

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

Methodology16 results

3DonPASCAL VOC 2007
MAP· 2016-11-24
42.8
best: 73.4 (WeakSAM-MIST-DINO (with SAM))
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
3DonPASCAL VOC 2012 test
MAP· 2016-11-24
37.9
best: 70.2 (WeakSAM-MIST-DINO (with SAM))
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
3DonImageNet
MAP· 2016-11-24
16.3
best: 19.6 (PCL-OB-G-Ens + FRCNN)
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
2D ClassificationonPASCAL VOC 2007
MAP· 2016-11-24
42.8
best: 73.4 (WeakSAM-MIST-DINO (with SAM))
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
2D ClassificationonPASCAL VOC 2012 test
MAP· 2016-11-24
37.9
best: 70.2 (WeakSAM-MIST-DINO (with SAM))
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
2D ClassificationonCOCO test-dev
AP50· 2016-11-24
12.3
best: 82.1 (Plain-DETR (Swin-L))
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
2D ClassificationonImageNet
MAP· 2016-11-24
16.3
best: 19.6 (PCL-OB-G-Ens + FRCNN)
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
2D Object DetectiononPASCAL VOC 2007
MAP· 2016-11-24
42.8
best: 73.4 (WeakSAM-MIST-DINO (with SAM))
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
2D Object DetectiononPASCAL VOC 2012 test
MAP· 2016-11-24
37.9
best: 70.2 (WeakSAM-MIST-DINO (with SAM))
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
2D Object DetectiononCOCO test-dev
AP50· 2016-11-24
12.3
best: 82.1 (Plain-DETR (Swin-L))
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
2D Object DetectiononImageNet
MAP· 2016-11-24
16.3
best: 19.6 (PCL-OB-G-Ens + FRCNN)
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
16konPASCAL VOC 2007
MAP· 2016-11-24
42.8
best: 73.4 (WeakSAM-MIST-DINO (with SAM))
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
16konPASCAL VOC 2012 test
MAP· 2016-11-24
37.9
best: 70.2 (WeakSAM-MIST-DINO (with SAM))
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
16konCOCO test-dev
AP50· 2016-11-24
12.3
best: 82.1 (Plain-DETR (Swin-L))
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
16konImageNet
MAP· 2016-11-24
16.3
best: 19.6 (PCL-OB-G-Ens + FRCNN)
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
3DonCOCO test-dev
AP50· 2016-11-24
12.3
best: 95 (ViTPose (ViTAE-G, ensemble))
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258

Computer Vision4 results

Object DetectiononPASCAL VOC 2007
MAP· 2016-11-24
42.8
best: 73.4 (WeakSAM-MIST-DINO (with SAM))
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
Object DetectiononPASCAL VOC 2012 test
MAP· 2016-11-24
37.9
best: 70.2 (WeakSAM-MIST-DINO (with SAM))
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
Object DetectiononCOCO test-dev
AP50· 2016-11-24
12.3
best: 82.1 (Plain-DETR (Swin-L))
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258
Object DetectiononImageNet
MAP· 2016-11-24
16.3
best: 19.6 (PCL-OB-G-Ens + FRCNN)
SOTA
Weakly Supervised Cascaded Convolutional Networks arXiv:1611.08258