Finetuning generative models on limited instance segmentation data produces zero-shot generalization to unseen object categories and styles, matching or exceeding supervised baselines like SAM on ambiguous boundaries.
Scaling properties of diffusion models for perceptual tasks.arXiv preprint arXiv:2411.08034,
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The serial scaling hypothesis formalizes inherently serial problems in complexity theory and demonstrates that diffusion models cannot solve them.
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gen2seg: Generative Models Enable Generalizable Instance Segmentation
Finetuning generative models on limited instance segmentation data produces zero-shot generalization to unseen object categories and styles, matching or exceeding supervised baselines like SAM on ambiguous boundaries.
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The Serial Scaling Hypothesis
The serial scaling hypothesis formalizes inherently serial problems in complexity theory and demonstrates that diffusion models cannot solve them.