Passive non-line-of-sight imaging for moving targets with an event camera

Non-line-of-sight (NLOS) imaging is an emerging technique for detecting objects behind obstacles or around corners. Recent studies on passive NLOS mainly focus steady-state measurement and reconstruction methods, which show limitations in recognition of moving targets. To the best our knowledge, we propose a novel event-based method. We acquire asynchronous data contains detailed dynamic information target, efficiently ease degradation speckle caused by movement. Besides, create first dataset, NLOS-ES, feature extracted time-surface representation. compare reconstructions through with frame-based data. The method performs well PSNR LPIPS, 20% 10% better than method, while volume takes only 2% traditional