pith:DOFPGUK7
In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer
Large Diffusion Transformers perform precise instructional image editing via in-context generation without major retraining.
arxiv:2504.20690 v3 · 2025-04-29 · cs.CV
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Claims
ICEdit achieves state-of-the-art editing performance with only 0.1% of the training data and 1% trainable parameters compared to previous methods.
That the inherent comprehension and generation abilities of large-scale Diffusion Transformers can be effectively leveraged for precise instructional editing through an in-context paradigm without any architectural modifications.
ICEdit achieves state-of-the-art instructional image editing in Diffusion Transformers via in-context generation, requiring only 0.1% of prior training data and 1% trainable parameters.
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| First computed | 2026-05-17T23:38:47.348564Z |
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| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
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| Schema | pith-number/v1.0 |
Canonical hash
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Canonical record JSON
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