REALM: An RGB- and Event-Aligned Latent Manifold for Cross-Modal Perception
Event cameras provide several unique advantages over standard frame-based sensors, including high temporal resolution, low latency, and robustness to extreme lighting. However, existing learning-based approaches for event processing are typically confined to narrow, task-specific silos and lack the ability to generalize across modalities. We address this gap with REALM, a cross-modal framework that learns an RGB- and Event-Aligned Latent Manifold by projecting event representations into the pretrained latent space of RGB foundation models. Instead of task-specific training, we leverage low-rank adaptation (LoRA) to bridge the modality gap, effectively unlocking the geometric and semantic ...
| Authors | Vincenzo Polizzi, David B. Lindell, Jonathan Kelly |
|---|---|
| Primary category | cs.CV |
| Published | 30 April 2026 |
| Last updated at source | 18 September 2026 |
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