A regret-based Pareto optimization jointly maximizes contrast map variance for event alignment and minimizes it for denoising, yielding better results than separate processing in experiments on denoising and motion estimation.
Event probability mask (epm) and event denoising convolutional neural network (edncnn) for neuromorphic cameras,
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Joint Alignment and Denoising for Event-Based Vision Sensors Using Regret-based Pareto Optimization
A regret-based Pareto optimization jointly maximizes contrast map variance for event alignment and minimizes it for denoising, yielding better results than separate processing in experiments on denoising and motion estimation.