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Federico Paredes-Valles

2 accepted papers

2025

On-Device Self-Supervised Learning of Low-Latency Monocular Depth from Only Events

CVPR 2025poster

Event cameras provide low-latency perception for only milliwatts of power. This makes them highly suitable for resource-restricted, agile robots such as small flying drones. Self-supervised learning based on contrast maximization holds great potential for event-based robot vision, as it foregoes the…

Cited by 0SourcePDFScholar
2021

Back to Event Basics: Self-Supervised Learning of Image Reconstruction for Event Cameras via Photometric Constancy

CVPR 2021poster

Event cameras are novel vision sensors that sample, in an asynchronous fashion, brightness increments with low latency and high temporal resolution. The resulting streams of events are of high value by themselves, especially for high speed motion estimation. However, a growing body of work has also…

Cited by 158PDFScholar