Large-Scale Dataset for Event-Based Object Recognition
The N-ImageNet dataset is an event-camera counterpart for the ImageNet dataset. The dataset is obtained by moving an event camera around a monitor displaying images from ImageNet. N-ImageNet contains approximately 1,300k training samples and 50k validation samples. In addition, the dataset also contains variants of the validation dataset recorded under a wide range of lighting or camera trajectories. Additional details about the dataset are explained in the paper available through this link. Please cite this paper if you make use of the dataset.
Variants: N-ImageNet, N-ImageNet (mini)
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Classification | Event Spike Tensor | N-ImageNet: Towards Robust, Fine-Grained Object … | 2021-12-02 |
| Classification | DiST | N-ImageNet: Towards Robust, Fine-Grained Object … | 2021-12-02 |
| Classification | Sorted Time Surface | N-ImageNet: Towards Robust, Fine-Grained Object … | 2021-12-02 |
| Classification | Event Histogram | N-ImageNet: Towards Robust, Fine-Grained Object … | 2021-12-02 |
| Classification | HATS | N-ImageNet: Towards Robust, Fine-Grained Object … | 2021-12-02 |
| Classification | Binary Event Image | N-ImageNet: Towards Robust, Fine-Grained Object … | 2021-12-02 |
| Classification | Timestamp Image | N-ImageNet: Towards Robust, Fine-Grained Object … | 2021-12-02 |
| Classification | Event Image | N-ImageNet: Towards Robust, Fine-Grained Object … | 2021-12-02 |
| Classification | Time Surface | N-ImageNet: Towards Robust, Fine-Grained Object … | 2021-12-02 |
Recent papers with results on this dataset: