Browse State-of-the-Art › Diffusion Personalization Tuning Free
Diffusion Personalization Tuning Free
9 papers with code · 1 benchmark · 1 dataset archive 2025-07-28
This is a sub-class of diffusion personalization methods where the model is not required to be tuned on few user-specific images. Rather, the diffusion models are additionally trained on some dataset to allow forward pass personalization during test time.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| AgeDB (7 rows) | Arc2Face | Arc2Face: A Foundation Model for ID-Consistent Human Faces | code | Syntology ran 1 of 4 samples · 3 unverified | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
1 dataset whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
9 shown of 9 papers with code (10 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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15 Jan 2024 4 repositories listed Syntology ran 8 of 10 samples · 2 unverifiedThere has been significant progress in personalized image synthesis with methods such as Textual Inversion, DreamBooth, and LoRA.
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13 Aug 2023 4 repositories listed Syntology ran 3 of 8 samples · 5 unverifiedDespite the simplicity of our method, an IP-Adapter with only 22M parameters can achieve comparable or even better performance to a fully fine-tuned image prompt model.
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18 Mar 2024 3 repositories listed Syntology ran 1 of 4 samples · 3 unverified · 3 pointer-only (licence)This paper presents Arc2Face, an identity-conditioned face foundation model, which, given the ArcFace embedding of a person, can generate diverse photo-realistic images with an unparalleled degree of face similarity…
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13 Jul 2023 2 repositories listed Syntology ran 0 of 7 samples · 7 unverifiedBy composing these weights into the diffusion model, coupled with fast finetuning, HyperDreamBooth can generate a person's face in various contexts and styles, with high subject details while also preserving the model's…
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26 Jan 2025 1 repository listedThe stories and characters that captivate us as we grow up shape unique fantasy worlds, with images serving as the primary medium for visually experiencing these realms.
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22 Jan 2024 1 repository listed Syntology ran 20 of 24 samples · 4 unverified · 14 pointer-only (licence)In this paper, we propose a brand new training-free text-to-image generation/editing framework, namely Recaption, Plan and Generate (RPG), harnessing the powerful chain-of-thought reasoning ability of multimodal LLMs to…
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7 Dec 2023 1 repository listed Syntology ran 3 of 5 samples · 2 unverified · 5 pointer-only (licence)Recent advances in text-to-image generation have made remarkable progress in synthesizing realistic human photos conditioned on given text prompts.
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21 Jul 2023 1 repository listed Syntology ran 4 of 8 samples · 4 unverifiedIn this paper, we propose Subject-Diffusion, a novel open-domain personalized image generation model that, in addition to not requiring test-time fine-tuning, also only requires a single reference image to support…
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17 May 2023 1 repository listed Syntology ran 6 of 17 samples · 11 unverifiedFastComposer proposes delayed subject conditioning in the denoising step to maintain both identity and editability in subject-driven image generation.
Syntology lines on 8 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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