Research map / Image generation / Editing and style transfer
Exploring the Effectiveness of Mask-Guided Feature Modulation as a Mechanism for Localized Style Editing of Real Images (Student Abstract)
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use mask-guided feature modulation instead of latent inversion for localized editing | SemanticStyle Autoencoder versus SemanticStyleGAN · One texture edit per ROI | time taken (s): 120.602 -> 0.01143 | Helped |
| Add the refinement block after coarse mask-guided style editing | SemanticStyle Autoencoder · Localized real image editing | style effect strength | Hurt |
Closest papers by meaning
- SemanticStyleGAN: Learning Compositional Generative Priors for Controllable Image Synthesis and Editing (CVPR 2022 · similarity 0.89)
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- Improving Editability in Image Generation with Layer-wise Memory (CVPR 2025 · similarity 0.86)
- EditInfinity: Image Editing with Binary-Quantized Generative Models (NeurIPS 2025 · similarity 0.86)
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