Papers › Pretraining is All You Need for Image-to-Image Translation

Pretraining is All You Need for Image-to-Image Translation

25 May 2022arXiv:2205.12952archive 2025-07-28

Tengfei Wang, Ting Zhang, Bo Zhang, Hao Ouyang, Dong Chen, Qifeng Chen, Fang Wen

We propose to use pretraining to boost general image-to-image translation. Prior image-to-image translation methods usually need dedicated architectural design and train individual translation models from scratch, struggling for high-quality generation of complex scenes, especially when paired training data are not abundant. In this paper, we regard each image-to-image translation problem as a downstream task and introduce a simple and generic framework that adapts a pretrained diffusion model to accommodate various kinds of image-to-image translation. We also propose adversarial training to enhance the texture synthesis in the diffusion model training, in conjunction with normalized guidance sampling to improve the generation quality. We present extensive empirical comparison across various tasks on challenging benchmarks such as ADE20K, COCO-Stuff, and DIODE, showing the proposed pretraining-based image-to-image translation (PITI) is capable of synthesizing images of unprecedented realism and faithfulness.

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Code

Syntology Ran 2 of 3 code samples harvested from 1 repository linked to this paper; 1 has no recorded run. Of those that ran: 1 ran · honoured contract; 1 ran · our draft was wrong.

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PITI-Synthesis/PITI officialmentioned on GitHubpytorch report
rinnakk/japanese-stable-diffusion mentioned on GitHubpytorchnot reachable when probed 2026-09-17 — repositories for recent papers often appear after camera-ready report

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Code Syntology ran Syntology

3 samples harvested; 2 ran; 1 honoured the contract we drafted; 1 has no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.

1ran · honoured contract
1ran · our draft was wrong
1unverified

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labelcolormap PITI-Synthesis/PITI/preprocess/preprocess_mask.py official repository ran · honoured contract MIT (permissive) · 10ccb87c1a7e34bc · report
uint82bin PITI-Synthesis/PITI/preprocess/preprocess_mask.py official repository ran · our draft was wrong MIT (permissive) · 098a8251265f82c2 · report
estimate PITI-Synthesis/PITI/preprocess/preprocess_sketch.py official repository unverified MIT (permissive) · 17279541625491ee · report

Tasks

AllImage-to-Image TranslationSketch-to-Image TranslationTexture SynthesisTranslation

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Image-to-Image Translation COCO-Stuff Labels-to-Photos PITI FID 15.6 #4 of 15 Archive leaderboard report
Sketch-to-Image Translation COCO-Stuff PITI FID 18.5 #1 of 3 Archive leaderboard report
Sketch-to-Image Translation COCO-Stuff PITI FID-C 7.6 #1 of 3 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

Diffusion

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