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Generative Adversarial Text to Image Synthesis
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add text-embedding interpolation regularization (ablation) | Text-conditional GAN · CUB zero-shot | visual plausibility | Helped |
| Add text-embedding interpolation regularization (ablation) | Text-conditional GAN · CUB zero-shot | reliability of plausible image generation | Helped |
| Use matching-aware discrimination with real images paired to mismatched text (ablation) | Text-conditional GAN · CUB | visual plausibility | No clear effect |
| Remove both matching-aware discrimination and interpolation regularization (ablation) | Text-conditional GAN · Oxford-102 Flowers | visual plausibility | No clear effect |
| Use matching-aware discrimination and interpolation regularization together (ablation) | Text-conditional GAN · CUB style verification | AU-ROC | Helped |
| Use GAN-CLS rather than AlignDRAW | Text-to-image synthesis · MS COCO | sample sharpness and resolution | Helped |
| Use AlignDRAW rather than GAN-CLS | Text-to-image synthesis · MS COCO | sensitivity to single-word changes | Helped |
Closest papers by meaning
- DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis (CVPR 2022 · similarity 0.91)
- DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-To-Image Synthesis (CVPR 2019 · similarity 0.90)
- Text to Image Generation With Semantic-Spatial Aware GAN (CVPR 2022 · similarity 0.90)
- Adversarial Text to Continuous Image Generation (CVPR 2024 · similarity 0.89)
- InstantPainting: Expanding GANs for Efficient Text-Conditioned Image Generation Platform (AAAI 2025 · similarity 0.86)
- Unlocking Pre-trained Image Backbones for Semantic Image Synthesis (CVPR 2024 · similarity 0.86)
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