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المنصة
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SOTA
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Object Detection On Lvis V1 0 Val
Object Detection On Lvis V1 0 Val
المقاييس
box AP
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
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اسم النموذج
box AP
Paper Title
Co-DETR (single-scale)
68.0
DETRs with Collaborative Hybrid Assignments Training
Grounding DINO 1.5 Pro
63.5
Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection
InternImage-H
63.2
InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions
EVA
62.2
EVA: Exploring the Limits of Masked Visual Representation Learning at Scale
RichSem (Focal-H + ImageNet as weakly-supervised extra data)
61.2
Learning from Rich Semantics and Coarse Locations for Long-tailed Object Detection
GLEE-Pro
55.7
General Object Foundation Model for Images and Videos at Scale
ViTDet-H
53.4
Exploring Plain Vision Transformer Backbones for Object Detection
DiverGen (Swin-L)
51.2
DiverGen: Improving Instance Segmentation by Learning Wider Data Distribution with More Diverse Generative Data
ViTDet-L
51.2
Exploring Plain Vision Transformer Backbones for Object Detection
CenterNet2 (Swin-L w/ X-Paste + Copy-Paste)
50.9
X-Paste: Revisiting Scalable Copy-Paste for Instance Segmentation using CLIP and StableDiffusion
Eff-B7 NAS-FPN (1280, Copy-Paste pre-training))
41.6
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation
R101-MaskRCNN-LOCE
29
Exploring Classification Equilibrium in Long-Tailed Object Detection
R50-MaskRCNN-LOCE
27.4
Exploring Classification Equilibrium in Long-Tailed Object Detection
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Object Detection On Lvis V1 0 Val | SOTA | HyperAI