Papers › Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models

Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models

8 Mar 2023CVPR 2023 1arXiv:2303.04803archive 2025-07-28

Jiarui Xu, Sifei Liu, Arash Vahdat, Wonmin Byeon, Xiaolong Wang, Shalini De Mello

We present ODISE: Open-vocabulary DIffusion-based panoptic SEgmentation, which unifies pre-trained text-image diffusion and discriminative models to perform open-vocabulary panoptic segmentation. Text-to-image diffusion models have the remarkable ability to generate high-quality images with diverse open-vocabulary language descriptions. This demonstrates that their internal representation space is highly correlated with open concepts in the real world. Text-image discriminative models like CLIP, on the other hand, are good at classifying images into open-vocabulary labels. We leverage the frozen internal representations of both these models to perform panoptic segmentation of any category in the wild. Our approach outperforms the previous state of the art by significant margins on both open-vocabulary panoptic and semantic segmentation tasks. In particular, with COCO training only, our method achieves 23.4 PQ and 30.0 mIoU on the ADE20K dataset, with 8.3 PQ and 7.9 mIoU absolute improvement over the previous state of the art. We open-source our code and models at https://github.com/NVlabs/ODISE .

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Code

nvlabs/odise officialmentioned in papermentioned on GitHubpytorchNOASSERTION report

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Tasks

Open Vocabulary Panoptic Segmentation Open Vocabulary Semantic Segmentation Open-World Instance Segmentation Panoptic Segmentation Segmentation Semantic Segmentation Zero Shot Segmentation

Results from the paper archive 2025-07-28

Task	Dataset	Model	Metric	Value	Rank at snapshot	Leaderboard	Report
Open Vocabulary Panoptic Segmentation	ADE20K	ODISE(Caption)	PQ	23.4	#7 of 10	Archive leaderboard	report
Open Vocabulary Panoptic Segmentation	ADE20K	ODISE (Label)	PQ	22.6	#8 of 10	Archive leaderboard	report
Open Vocabulary Semantic Segmentation	ADE20K-150	ODISE	mIoU	29.9	#16 of 23	Archive leaderboard	report
Open Vocabulary Semantic Segmentation	ADE20K-847	ODISE	mIoU	11.1	#16 of 19	Archive leaderboard	report
Open Vocabulary Semantic Segmentation	PASCAL Context-459	ODISE	mIoU	14.5	#13 of 15	Archive leaderboard	report
Open Vocabulary Semantic Segmentation	PASCAL Context-59	ODISE	mIoU	57.3	#14 of 24	Archive leaderboard	report
Open Vocabulary Semantic Segmentation	PascalVOC-20	ODISE	mIoU	84.6	#15 of 20	Archive leaderboard	report
Open-World Instance Segmentation	UVO	ODISE	ARmask	57.7	#2 of 2	Archive leaderboard	report
Zero Shot Segmentation	Segmentation in the Wild	odise	Mean AP	38.7	#6 of 12	Archive leaderboard	report

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Methods

CLIP Diffusion

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