Unsupervised Keypoints from Pretrained Diffusion Models
Eric Hedlin, Gopal Sharma, Shweta Mahajan, Xingzhe He, Hossam Isack, Abhishek Kar, Helge Rhodin, Andrea Tagliasacchi, Kwang Moo Yi
2024年份
16顶会引用
摘要
https://stablekeypoints.github.io/ Image dataset Randomly initialized tokens Optimized tokens Estimated keypoints Localize Figure 1. Teaser -we propose an unsupervised method to learn keypoints based on optimizing text embeddings of latent diffusion models [44]. Our method is motivated by the fact that random text tokens already respond roughly consistently to semantically similar regions. By promoting localization we obtain unsupervised keypoints that outperform the state-of-the-art.
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引用它的顶会 Paper16
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- Scene-Level Appearance Transfer with Semantic CorrespondencesLiyuan Zhu, Shengqu Cai, Shengyu Huang, Gordon Wetzstein 等SIGGRAPH 2025 · 被引用 3 次
- : Symmetry Understanding of 3D Shapes via Chirality DisentanglementWeikang Wang, Tobias Weißberg, Nafie El Amrani, Florian BernardICCV 2025 · 被引用 3 次
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它引用的顶会 Paper23
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser 等CVPR 2022 · 被引用 13,123 次
- Photorealistic Text-to-Image Diffusion Models with Deep Language UnderstandingChitwan Saharia, William Chan, Saurabh Saxena, Lala Li 等NeurIPS 2022 · 被引用 8,965 次
- Improved Denoising Diffusion Probabilistic ModelsAlexander Quinn Nichol, Prafulla DhariwalICML 2021 · 被引用 5,234 次
- DiffusionDet: Diffusion Model for Object DetectionShoufa Chen, Peize Sun, Yibing Song, Ping LuoICCV 2023 · 被引用 715 次
- Label-Efficient Semantic Segmentation with Diffusion ModelsDmitry Baranchuk, Andrey Voynov, Ivan Rubachev, Valentin Khrulkov 等ICLR 2022 · 被引用 700 次
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