June 6, 2024, 4:49 a.m. | Paul Couairon, Mustafa Shukor, Jean-Emmanuel Haugeard, Matthieu Cord, Nicolas Thome

cs.CV updates on arXiv.org arxiv.org

arXiv:2406.02842v1 Announce Type: new
Abstract: Foundation models have emerged as powerful tools across various domains including language, vision, and multimodal tasks. While prior works have addressed unsupervised image segmentation, they significantly lag behind supervised models. In this paper, we use a diffusion UNet encoder as a foundation vision encoder and introduce DiffCut, an unsupervised zero-shot segmentation method that solely harnesses the output features from the final self-attention block. Through extensive experimentation, we demonstrate that the utilization of these diffusion features …

arxiv cs.cv diffusion features image recursive segmentation type via zero-shot

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