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Lightweight Generative Adversarial Networks for Text-Guided Image Manipulation

NeurIPS 2020 · Image generation › GANs · approach: Large-scale GAN latent analysis · 11 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use the proposed word-level discriminator instead of removing it (ablation)Lightweight GAN · CUBFID: 9.20 -> 8.02Helped
use the proposed word-level discriminator instead of removing it (ablation)Lightweight GAN · COCOFID: 15.60 -> 12.39Helped
use the proposed word-level discriminator instead of a text-adaptive discriminator (ablation)Lightweight GAN · CUBFID: 8.84 -> 8.02Helped
use the proposed word-level discriminator instead of a text-adaptive discriminator (ablation)Lightweight GAN · COCOFID: 14.95 -> 12.39Helped
use the proposed word-level discriminator instead of the ControlGAN word-level discriminator (ablation)Lightweight GAN · CUBFID: 8.72 -> 8.02Helped
use the proposed word-level discriminator instead of the ControlGAN word-level discriminator (ablation)Lightweight GAN · COCOFID: 13.68 -> 12.39Helped
reduce model size to the reported Ours* configuration (ablation)Lightweight GAN · CUBgenerator parameters: 18.5M -> 5.4MHelped
reduce model size to the reported Ours* configuration (ablation)Lightweight GAN · COCOgenerator parameters: 30.1M -> 7.4MHelped
use the lightweight proposed architecture rather than ManiGANText-guided image manipulation · CUBFID: 9.75 -> 8.02Helped
use the lightweight proposed architecture rather than ManiGANText-guided image manipulation · COCOFID: 25.08 -> 12.39Helped

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