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.
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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.