N-ImageNet (Large-Scale Dataset for Event-Based Object Recognition)
Introduced by Kim et al. in N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras
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.
Benchmarks
| Trend | Task | Dataset Variant | Best Model | Paper | Code |
|---|---|---|---|---|---|
|
N-ImageNet
|
Sorted Time Surface + Ev-TTA
|
|||
|
N-ImageNet
|
Event Spike Tensor
|
|||
|
N-ImageNet (mini)
|
Event Imge
|
Papers
| Paper | Code | Results | Date | Stars |
|---|
