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Event Cameras, Contrast Maximization and Reward Functions: An Analysis

CVPR 2019 · Time series › Causal and generative time series · approach: Generative temporal point processes · 93 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Combine sparsity-rewarding and magnitude-rewarding criteria in rR1 (ablation)Contrast maximization optical flow · Line segment sequence, E/N 1/0mean absolute magnitude error: 38.29 -> 10.31Helped
Add rSoE refinement to rR1 to form rR2 (ablation)Contrast maximization optical flow · Line segment sequence, E/N 1/10mean absolute magnitude error: 55.33 -> 37.48Helped
Use the hybrid reward rather than rSoS (ablation)Contrast maximization optical flow · Circle sequence, E/N 1/0mean absolute magnitude error: 0.49 -> 1.69Hurt
Use rR2 instead of rSoS (ablation)Contrast maximization optical flow · Circle sequence, E/N 1/10mean absolute magnitude error: 43.41 -> 5.29Helped
Combine reward types in rR2 (ablation)Contrast maximization optical flow · Office sequence, E/N 1/0mean absolute magnitude error: 5.58 -> 4.95Helped
Add rSoE refinement to rR1 to form rR2 (ablation)Contrast maximization optical flow · Office sequence, E/N 1/0mean absolute magnitude error: 9.09 -> 4.95Helped
Use the hybrid reward instead of individual reward types (ablation)Contrast maximization optical flow · Bicycle sequence, natural noisemean absolute magnitude error: 22.12 -> 8.83Helped
Use magnitude-rewarding rather than sparsity-rewarding rewards (ablation)Contrast maximization optical flow · Noisy event streamsmean absolute magnitude errorMixed
Use sparsity-rewarding rather than magnitude-rewarding rewards (ablation)Contrast maximization optical flow · Line segment sequence with aperture uncertaintymean absolute magnitude error: 38.29 -> 11.36Helped
Use rSoE or rMoA in a noisy circle sequence (ablation)Contrast maximization optical flow · Circle sequence, E/N 1/10mean absolute magnitude error: 72.14 -> 23.56; 73.45 -> 11.10Helped

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