eBIRD: Event-based Intensity Image Reconstruction Using Controllable Diffusion Models
Intensity-image reconstruction from event streams remains a challenging problem due to the binary, sparse, and asynchronous nature of event data. This work proposes eBIRD, an event-guided reconstruction framework that combines a DDPM with ControlNet-based conditioning. We analyze generic and specialized diffusion learning strategies for handwritten digit (N-MNIST) and face (RGBE-Gaze) reconstruction using 33ms event windows. On N-MNIST, the general model achieves the best reconstruction quality (MSE 0.0052, SSIM 0.8982, PSNR 23.34dB), whereas the specialized model performs best on RGBE-Gaze (MSE 0.0161, SSIM 0.7605, PSNR 19.08dB). These preliminary results suggest that controllable diffus...
| Authors | Ignacio Bugueno-Cordova, Fabian Valderrama, Rodrigo Verschae |
|---|---|
| Primary category | cs.CV |
| Published | 9 August 2026 |
| Last updated at source | 9 August 2026 |
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