HyperAI
HyperAI
الرئيسية
المنصة
الوثائق
الأخبار
الأوراق البحثية
الدروس
مجموعات البيانات
الموسوعة
SOTA
نماذج LLM
لوحة الأداء GPU
الفعاليات
البحث
حول
شروط الخدمة
سياسة الخصوصية
العربية
HyperAI
HyperAI
Toggle Sidebar
البحث في الموقع...
⌘
K
Command Palette
Search for a command to run...
المنصة
الرئيسية
SOTA
تمييز النموذج
Instance Segmentation On Lvis V1 0 Val
Instance Segmentation On Lvis V1 0 Val
المقاييس
mask AP
mask APr
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
mask AP
mask APr
Paper Title
Co-DETR (single-scale)
60.7
-
DETRs with Collaborative Hybrid Assignments Training
EVA
55.0
-
EVA: Exploring the Limits of Masked Visual Representation Learning at Scale
HTC-ealrystop-ema
50.4
-
LVIS Challenge Track Technical Report 1st Place Solution: Distribution Balanced and Boundary Refinement for Large Vocabulary Instance Segmentation
GLEE-Pro
49.9
-
General Object Foundation Model for Images and Videos at Scale
ViTDet-H
48.1
36.9
Exploring Plain Vision Transformer Backbones for Object Detection
ViTDet-L
46.0
34.3
Exploring Plain Vision Transformer Backbones for Object Detection
DiverGen (Swin-L)
45.5
45.8
DiverGen: Improving Instance Segmentation by Learning Wider Data Distribution with More Diverse Generative Data
CenterNet2 (Swin-L w/ X-Paste + Copy-Paste)
45.4
43.8
X-Paste: Revisiting Scalable Copy-Paste for Instance Segmentation using CLIP and StableDiffusion
DiffusionInst-SwinL
38.6
-
DiffusionInst: Diffusion Model for Instance Segmentation
Eff-B7 NAS-FPN (1280, Copy-Paste pre-training))
38.1
-
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation
DiffusionInst-SwinB
36
-
DiffusionInst: Diffusion Model for Instance Segmentation
FRACAL-SwinS
33.6
27.8
Fractal Calibration for long-tailed object detection
SE-R101-FPN-MaskRCNN-APA
30.7
23.6
Adaptive Parametric Activation
FRACAL-SwinT
30.7
25.7
Fractal Calibration for long-tailed object detection
SE-R50-FPN-MaskRCNN-APA
29.1
21.6
Adaptive Parametric Activation
R101-FPN-MaskRCNN-GOL
29.0
-
Long-tailed Instance Segmentation using Gumbel Optimized Loss
Cascade-R101-EQLv2
28.8
-
Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object Detection
R101-MaskRCNN-LOCE
28
-
Exploring Classification Equilibrium in Long-Tailed Object Detection
R50-FPN-MaskRCNN-GOL
27.7
-
Long-tailed Instance Segmentation using Gumbel Optimized Loss
R101-FPN-MaskRCNN-EQLv2
27.5
-
Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object Detection
0 of 24 row(s) selected.
Previous
Next
Instance Segmentation On Lvis V1 0 Val | SOTA | HyperAI