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Models/ViTDet-L

ViTDet-L

Reported on 7 benchmarks across 6 tasks · 1 paper

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

Methodology4 results

3DonLVIS v1.0 val
box AP· 2022-03-30
51.2
best: 68 (Co-DETR (single-scale))
Exploring Plain Vision Transformer Backbones for Object Detection arXiv:2203.16527
2D ClassificationonLVIS v1.0 val
box AP· 2022-03-30
51.2
best: 68 (Co-DETR (single-scale))
Exploring Plain Vision Transformer Backbones for Object Detection arXiv:2203.16527
2D Object DetectiononLVIS v1.0 val
box AP· 2022-03-30
51.2
best: 68 (Co-DETR (single-scale))
Exploring Plain Vision Transformer Backbones for Object Detection arXiv:2203.16527
16konLVIS v1.0 val
box AP· 2022-03-30
51.2
best: 68 (Co-DETR (single-scale))
Exploring Plain Vision Transformer Backbones for Object Detection arXiv:2203.16527

Computer Vision3 results

Object DetectiononLVIS v1.0 val
box AP· 2022-03-30
51.2
best: 68 (Co-DETR (single-scale))
Exploring Plain Vision Transformer Backbones for Object Detection arXiv:2203.16527
Instance SegmentationonLVIS v1.0 val
mask AP· 2022-03-30
46
best: 60.7 (Co-DETR (single-scale))
Exploring Plain Vision Transformer Backbones for Object Detection arXiv:2203.16527
Instance SegmentationonLVIS v1.0 val
mask APr· 2022-03-30
34.3
best: 45.8 (DiverGen (Swin-L))
Exploring Plain Vision Transformer Backbones for Object Detection arXiv:2203.16527