| Co-DETR (single-scale) |
- mask AP
- 60.7
|
DETRs with Collaborative Hybrid Assignments Training 2022-11-22 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 |
| EVA |
- mask AP
- 55.0
|
EVA: Exploring the Limits of Masked Visual Representation Learning at Scale 2022-11-14 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 |
| HTC-ealrystop-ema |
- mask AP
- 50.4
|
LVIS Challenge Track Technical Report 1st Place Solution: Distribution Balanced and Boundary Refinement for Large Vocabulary Instance Segmentation 2021-11-04 |
연결 없음 |
| GLEE-Pro |
- mask AP
- 49.9
|
General Object Foundation Model for Images and Videos at Scale 2023-12-14 |
코드 1 |
| ViTDet-H |
- mask AP
- 48.1
- mask APr
- 36.9
|
Exploring Plain Vision Transformer Backbones for Object Detection 2022-03-30 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 · 코드 10 · 코드 11 |
| ViTDet-L |
- mask AP
- 46.0
- mask APr
- 34.3
|
Exploring Plain Vision Transformer Backbones for Object Detection 2022-03-30 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 · 코드 10 · 코드 11 |
| DiverGen (Swin-L) |
- mask AP
- 45.5
- mask APr
- 45.8
|
DiverGen: Improving Instance Segmentation by Learning Wider Data Distribution with More Diverse Generative Data 2024-05-16 |
코드 1 |
| CenterNet2 (Swin-L w/ X-Paste + Copy-Paste) |
- mask AP
- 45.4
- mask APr
- 43.8
|
X-Paste: Revisiting Scalable Copy-Paste for Instance Segmentation using CLIP and StableDiffusion 2022-12-07 |
코드 1 · 코드 2 |
| DiffusionInst-SwinL |
- mask AP
- 38.6
|
DiffusionInst: Diffusion Model for Instance Segmentation 2022-12-06 |
코드 1 · 코드 2 |
| FRACAL-Swin-B |
- mask AP
- 38.5
- mask APr
- 35.5
|
Fractal Calibration for long-tailed object detection 2024-10-15 |
코드 1 |
| Eff-B7 NAS-FPN (1280, Copy-Paste pre-training)) |
- mask AP
- 38.1
|
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation 2020-12-13 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 |
| DiffusionInst-SwinB |
- mask AP
- 36
|
DiffusionInst: Diffusion Model for Instance Segmentation 2022-12-06 |
코드 1 · 코드 2 |
| FRACAL-SwinS |
- mask AP
- 33.6
- mask APr
- 27.8
|
Fractal Calibration for long-tailed object detection 2024-10-15 |
코드 1 |
| FRACAL-SwinT |
- mask AP
- 30.7
- mask APr
- 25.7
|
Fractal Calibration for long-tailed object detection 2024-10-15 |
코드 1 |
| SE-R101-FPN-MaskRCNN-APA |
- mask AP
- 30.7
- mask APr
- 23.6
|
Adaptive Parametric Activation 2024-07-11 |
코드 1 |
| SE-R50-FPN-MaskRCNN-APA |
- mask AP
- 29.1
- mask APr
- 21.6
|
Adaptive Parametric Activation 2024-07-11 |
코드 1 |
| R101-FPN-MaskRCNN-GOL |
- mask AP
- 29.0
|
Long-tailed Instance Segmentation using Gumbel Optimized Loss 2022-07-22 |
코드 1 |
| Cascade-R101-EQLv2 |
- mask AP
- 28.8
|
Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object Detection 2020-12-15 |
코드 1 · 코드 2 |
| R101-MaskRCNN-LOCE |
- mask AP
- 28
|
Exploring Classification Equilibrium in Long-Tailed Object Detection 2021-08-17 |
코드 1 |
| R50-FPN-MaskRCNN-GOL |
- mask AP
- 27.7
|
Long-tailed Instance Segmentation using Gumbel Optimized Loss 2022-07-22 |
코드 1 |
| R101-FPN-MaskRCNN-EQLv2 |
- mask AP
- 27.5
|
Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object Detection 2020-12-15 |
코드 1 · 코드 2 |
| DiffusionInst-ResNet101 |
- mask AP
- 27
|
DiffusionInst: Diffusion Model for Instance Segmentation 2022-12-06 |
코드 1 · 코드 2 |
| R50-MaskRCNN-LOCE |
- mask AP
- 26.6
|
Exploring Classification Equilibrium in Long-Tailed Object Detection 2021-08-17 |
코드 1 |
| R50-FPN-MaskRCNN-EQLv2 |
- mask AP
- 23.7
|
Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object Detection 2020-12-15 |
코드 1 · 코드 2 |
| DiffusionInst-ResNet50 |
- mask AP
- 22.3
|
DiffusionInst: Diffusion Model for Instance Segmentation 2022-12-06 |
코드 1 · 코드 2 |