| Paper | Code | Accuracy (%) | Architecture | Representation | Representation Time( ms / 100ms events) | Inference Time | Params (M) | ModelName | ReleaseDate |
|---|---|---|---|---|---|---|---|---|---|
| Masked Event Modeling: Self-Supervised Pretraining for Event Cameras | ✓ Link | 98.55 | Transformer | Event Histogram | MEM | 2022-12-20 | |||
| GET: Group Event Transformer for Event-Based Vision | ✓ Link | 96.7 | Transformer | Token | 4.5 | GET | 2023-10-04 | ||
| End-to-End Learning of Representations for Asynchronous Event-Based Data | ✓ Link | 92.5 | CNN | EST | 0.38 | 6.47 | 21.8 | ResNet34 + EST | 2019-04-17 |
| Object Detection with Spiking Neural Networks on Automotive Event Data | ✓ Link | 92.4 | SNN | VoxelCube | 9.23 | Spiking VGG-11 | 2022-05-09 | ||
| Object Detection with Spiking Neural Networks on Automotive Event Data | ✓ Link | 91.7 | SNN | VoxelCube | 18.81 | Spiking MobileNet-64 | 2022-05-09 | ||
| Object Detection with Spiking Neural Networks on Automotive Event Data | ✓ Link | 90.4 | SNN | VoxelCube | 3.93 | Spiking DenseNet121-24 | 2022-05-09 |