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Models/iBOT (ViT-B/16)

iBOT (ViT-B/16)

Reported on 8 benchmarks across 8 tasks · 1 paper

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

Methodology4 results

3DonCOCO test-dev
box mAP· 2021-11-15
51.2
best: 66 (Co-DETR)
iBOT: Image BERT Pre-Training with Online Tokenizer arXiv:2111.07832
2D ClassificationonCOCO test-dev
box mAP· 2021-11-15
51.2
best: 66 (Co-DETR)
iBOT: Image BERT Pre-Training with Online Tokenizer arXiv:2111.07832
2D Object DetectiononCOCO test-dev
box mAP· 2021-11-15
51.2
best: 66 (Co-DETR)
iBOT: Image BERT Pre-Training with Online Tokenizer arXiv:2111.07832
16konCOCO test-dev
box mAP· 2021-11-15
51.2
best: 66 (Co-DETR)
iBOT: Image BERT Pre-Training with Online Tokenizer arXiv:2111.07832

Computer Vision2 results

Object DetectiononCOCO test-dev
box mAP· 2021-11-15
51.2
best: 66 (Co-DETR)
iBOT: Image BERT Pre-Training with Online Tokenizer arXiv:2111.07832
Instance SegmentationonCOCO test-dev
mask AP· uses extra data· 2021-11-15
44.2
best: 57.1 (Co-DETR)
iBOT: Image BERT Pre-Training with Online Tokenizer arXiv:2111.07832

Medical1 result

Semantic SegmentationonADE20K
Validation mIoU· 2021-11-15
50
best: 63.6 (ViT-P (InternImage-H))
iBOT: Image BERT Pre-Training with Online Tokenizer arXiv:2111.07832

Audio1 result

10-shot image generationonADE20K
Validation mIoU· 2021-11-15
50
best: 63.6 (ViT-P (InternImage-H))
iBOT: Image BERT Pre-Training with Online Tokenizer arXiv:2111.07832