Browse State-of-the-Art › Conditional Text-to-Image Synthesis
Conditional Text-to-Image Synthesis
8 papers with code · 3 benchmarks · 2 datasets archive 2025-07-28
Introducing extra conditions based on the text-to-image generation process, similar to the paradigm of ControlNet.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
3 leaderboard tables shown for this task, 3 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 |
|---|---|---|---|---|---|
| MIMIC-CXR (13 rows) | Sana | CheXGenBench: A Unified Benchmark For Fidelity, Privacy and... | code | — | Compare |
| COCO 2017 val (12 rows) | LCDG | LaCon: Late-Constraint Diffusion for Steerable Guided Image Synthesis | code | — | Compare |
| COCO-MIG (5 rows) | MIGC | MIGC: Multi-Instance Generation Controller for Text-to-Image Synthesis | code | Syntology ran 8 of 9 samples · 1 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
2 datasets 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
8 shown of 8 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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20 Jul 2023 2 repositories listed Syntology ran 4 of 5 samples · 1 unverified · 5 pointer-only (licence)As such paired data is time-consuming and labor-intensive to acquire and restricted to a closed set, this potentially becomes the bottleneck for applications in an open world.
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15 May 2025 1 repository listedAdditionally, we release a high-quality, synthetic dataset, SynthCheX-75K, comprising 75K radiographs generated by the top-performing model (Sana 0.
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6 Jun 2024 1 repository listed Syntology ran 0 of 1 samples · 1 unverifiedWe present Zero-Painter, a novel training-free framework for layout-conditional text-to-image synthesis that facilitates the creation of detailed and controlled imagery from textual prompts.
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8 Feb 2024 1 repository listed Syntology ran 8 of 9 samples · 1 unverified · 9 pointer-only (licence)Lastly, we aggregate all the shaded instances to provide the necessary information for accurately generating multiple instances in stable diffusion (SD).
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5 Feb 2024 1 repository listed Syntology ran 17 of 18 samples · 1 unverifiedText-to-image diffusion models produce high quality images but do not offer control over individual instances in the image.
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25 May 2023 1 repository listedText-to-image (T2I) research has grown explosively in the past year, owing to the large-scale pre-trained diffusion models and many emerging personalization and editing approaches.
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19 May 2023 1 repository listedTo offer more controllability for the generation process, existing studies, termed as early-constraint methods in this paper, leverage extra conditions and incorporate them into pre-trained diffusion models.
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17 Jan 2023 1 repository listed Syntology ran 2 of 2 samples · 0 unverifiedLarge-scale text-to-image diffusion models have made amazing advances.
Syntology lines on 5 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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