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DefogGAN: Predicting Hidden Information in the StarCraft Fog of War with Generative Adversarial Nets

AAAI 2020 · Image generation › GANs · approach: Stabilized GAN training · 5 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add DefogGAN's predictive generator to accumulated-observation baselineStarCraft defogging · StarCraft test setMSE: 0.00370 -> 0.00208Helped
Add DefogGAN's predictive generator to accumulated-observation baselineStarCraft defogging · StarCraft test setF1: 0.850 -> 0.856No clear effect
Use DefogGAN instead of CEDStarCraft defogging · StarCraft test setF1: 0.682 -> 0.856Helped
Add current partial observation (ablation)DefogGAN · StarCraft test setMSE: 0.00293 -> 0.00208Helped
Add accumulated past partial observation (ablation)DefogGAN · StarCraft test setMSE: 0.00426 -> 0.00208Helped
Add adversarial loss (ablation)DefogGAN · StarCraft test setF1: 0.662 -> 0.856Helped
Add reconstruction loss (ablation)DefogGAN · StarCraft test setMSE: 1.73986 -> 0.00208Helped
Use pyramidal reconstruction loss instead of L2 loss (ablation)DefogGAN · StarCraft test setMSE: 0.00210 -> 0.00208Helped
Add observation-preserving connection (ablation)DefogGAN · StarCraft test setF1: 0.516 -> 0.856Helped
Train with different amounts of replay frames (ablation)DefogGAN · StarCraft test set, 5s–600s training intervalsMSE: 0.00211; 0.00208; 0.00215; 0.00213; 0.00230Mixed

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