A self-supervised spiking neural network framework estimates optical flow from asynchronous underwater event streams without labeled data, achieving competitive accuracy with high computational efficiency.
Dark-EvGS: event camera as an eye for radiance field in the dark
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
A dual-modal frame-event approach delivers real-time high-frame-rate binarization for silhouettes in dynamic scenes on CPU-only hardware by exploiting neuromorphic event data to reduce motion blur.
citing papers explorer
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Aquatic Neuromorphic Optical Flow
A self-supervised spiking neural network framework estimates optical flow from asynchronous underwater event streams without labeled data, achieving competitive accuracy with high computational efficiency.
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See Silhouettes in Motion with Neuromorphic Vision
A dual-modal frame-event approach delivers real-time high-frame-rate binarization for silhouettes in dynamic scenes on CPU-only hardware by exploiting neuromorphic event data to reduce motion blur.