OpenImages V6 is a large-scale dataset ,
consists of 9 million training images, 41,620 validation
samples, and 125,456 test samples. It is a partially annotated dataset, with 9,600 trainable classes
Variants: OpenImages-v6
This dataset is used in 2 benchmarks:
| Task | Model | Paper | Date |
|---|---|---|---|
| Object Detection | ScaleDet | ScaleDet: A Scalable Multi-Dataset Object … | 2023-06-08 |
| Object Detection | InternImage-H | InternImage: Exploring Large-Scale Vision Foundation … | 2022-11-10 |
| Multi-Label Classification | TResNet-M | ML-Decoder: Scalable and Versatile Classification … | 2021-11-25 |
| Multi-Label Classification | TResNet-L | Multi-label Classification with Partial Annotations … | 2021-10-21 |
| Multi-Label Classification | TResNet-M | Multi-label Classification with Partial Annotations … | 2021-10-21 |
| Multi-Label Classification | TResNet-L | Asymmetric Loss For Multi-Label Classification | 2020-09-29 |
Recent papers with results on this dataset: