Research map / Image generation / Autoregressive and latent generation
Semantic Pyramid for Image Generation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Generate from progressively deeper VGG feature levels instead of Conv1 features | Semantic Pyramid · Places365 test | FID: 2.89 -> 8.67 -> 11.08 -> 17.64 -> 19.59 -> 22.67 -> 29.34 | Hurt |
| Generate from deeper semantic feature levels rather than fine features | Semantic Pyramid · Places365 image generation | reference fidelity and sample diversity | Mixed |
Closest papers by meaning
- Linear Semantics in Generative Adversarial Networks (CVPR 2021 · similarity 0.92)
- Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis (NeurIPS 2019 · similarity 0.91)
- Unlocking Pre-trained Image Backbones for Semantic Image Synthesis (CVPR 2024 · similarity 0.90)
- Constrained Generative Adversarial Networks for Interactive Image Generation (CVPR 2019 · similarity 0.89)
- Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation (CVPR 2020 · similarity 0.89)
- Edge Guided GANs with Contrastive Learning for Semantic Image Synthesis (ICLR 2023 · similarity 0.89)
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