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GitHub / VisualComputingInstitute / diffusion-e2e-ft

Fine-Tuning Image-Conditional Diffusion Models is Easier than You Think. Accepted to WACV 2025 and NeurIPS AFM Workshop.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VisualComputingInstitute%2Fdiffusion-e2e-ft

Stars: 330
Forks: 4
Open issues: 0

License: None
Language: Python
Size: 8.82 MB
Dependencies parsed at: Pending

Created at: 8 months ago
Updated at: 5 months ago
Pushed at: 5 months ago
Last synced at: 5 months ago

Topics: diffusion, in-the-wild, monocular-depth-estimation, monocular-normals-estimation, single-step, zero-shot

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