SOTA Vision Foundation Models Leaderboard (08/Sep/2024)
Table of Contents
- Overview
- Image Classification Leaderboard
- Object Detection Leaderboard
- Instance Segmentation Leaderboard
Overview
Ranking of Vision Foundation Models by Task.
- Last update: (26/Sep/2024)
Image Classification Leaderboard
| Rank |
Model Name |
Architecture |
Pretraining Data |
Accuracy |
Parameters |
Datasets |
Release Date |
| 1 |
ViT-G/14 |
Vision Transformer (ViT) |
JFT-3B |
90.3% |
6.5B |
ImageNet-1k, ImageNet-21k |
2022 |
| 2 |
Swin Transformer |
Hierarchical Transformer |
ImageNet-22k |
88.4% |
197M |
ImageNet-1k, COCO |
2021 |
| 3 |
ConvNeXt |
Convolution-based Model |
ImageNet-22k |
87.8% |
350M |
ImageNet-1k |
2022 |
| 4 |
DeiT-III |
Data-efficient ViT |
ImageNet-1k |
87.1% |
87M |
ImageNet-1k |
2021 |
| 5 |
EfficientNetV2 |
EfficientNet Architecture |
ImageNet-21k |
85.7% |
480M |
ImageNet-1k |
2021 |
| 6 |
ResNet-RS |
Residual Networks |
ImageNet-1k |
85.2% |
100M |
ImageNet-1k |
2021 |
| 7 |
CoAtNet |
Convolution-Attention Hybrid |
ImageNet-22k |
84.9% |
366M |
ImageNet-1k |
2021 |
| 8 |
NFNet-F6 |
Normalizer-Free Network |
ImageNet-1k |
86.5% |
438M |
ImageNet-1k |
2021 |
| 9 |
MLP-Mixer |
MLP-based Vision Model |
ImageNet-1k |
85.3% |
59M |
ImageNet-1k |
2021 |
| 10 |
RegNetY |
Regularization Networks |
ImageNet-1k |
85.4% |
145M |
ImageNet-1k |
2021 |
Object Detection Leaderboard
| Rank |
Model Name |
Architecture |
Backbone |
mAP (COCO) |
Params |
GFLOPs |
Datasets |
Release Date |
| 1 |
Swin-L |
Swin Transformer |
Swin-L |
58.7 |
284M |
1382 |
COCO |
2021 |
| 2 |
DETR |
End-to-End Detection Transformer |
ResNet-50 |
48.1 |
41M |
86 |
COCO |
2020 |
| 3 |
YOLOv7 |
You Only Look Once |
CSP-Darknet53 |
56.8 |
67M |
18 |
COCO |
2022 |
| 4 |
EfficientDet-D7 |
EfficientNet Backbone |
EfficientNet |
52.2 |
51M |
325 |
COCO |
2020 |
| 5 |
Cascade Mask R-CNN |
CNN + Cascade |
ResNet-101 |
53.3 |
101M |
390 |
COCO |
2019 |
| 6 |
Faster R-CNN |
CNN + Region Proposal |
ResNet-50 |
42.1 |
41M |
184 |
COCO |
2017 |
| 7 |
CenterNet |
Center-based Detection |
Hourglass-104 |
47.0 |
202M |
630 |
COCO |
2020 |
| 8 |
FCOS |
Fully Convolutional Detection |
ResNeXt-101 |
45.2 |
64M |
128 |
COCO |
2019 |
| 9 |
YOLOv4 |
You Only Look Once |
CSP-Darknet53 |
51.5 |
65M |
117 |
COCO |
2020 |
| 10 |
RetinaNet |
Focal Loss-based Detection |
ResNet-101 |
40.1 |
56M |
96 |
COCO |
2018 |
Instance Segmentation Leaderboard
| Rank |
Model Name |
Architecture |
Backbone |
AP (COCO) |
Params |
GFLOPs |
Datasets |
Release Date |
| 1 |
Swin-L Mask R-CNN |
Swin Transformer |
Swin-L |
53.8 |
284M |
1382 |
COCO |
2021 |
| 2 |
Cascade Mask R-CNN |
Cascade CNN |
ResNet-101 |
50.2 |
101M |
390 |
COCO |
2019 |
| 3 |
SOLOv2 |
Segment Objects by Locations |
ResNet-50 |
42.1 |
34M |
113 |
COCO |
2020 |
| 4 |
Mask R-CNN |
Region Proposal + CNN |
ResNet-101 |
39.8 |
101M |
296 |
COCO |
2017 |
| 5 |
PointRend |
Point-based Segmentation |
ResNet-50 |
41.2 |
46M |
96 |
COCO |
2020 |
| 6 |
HTC |
Hybrid Task Cascade |
ResNet-101 |
43.6 |
128M |
400 |
COCO |
2019 |
| 7 |
YOLACT++ |
Real-time Instance Segmentation |
ResNet-101 |
31.2 |
74M |
100 |
COCO |
2019 |
| 8 |
CondInst |
Conditional Instance Segmentation |
ResNet-50 |
39.1 |
31M |
73 |
COCO |
2020 |
| 9 |
TensorMask |
Mask Head CNN |
ResNet-101 |
37.1 |
130M |
430 |
COCO |
2019 |
| 10 |
DeepLabV3+ |
Atrous CNN for Segmentation |
Xception-71 |
35.4 |
43M |
100 |
COCO |
2018 |