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Bridging Generative and Discriminative Models for Unified Visual Perception with Diffusion Priors
Our purpose is to establish a unified visual perception framework, capitalizing on the potential synergies between generative and discriminative models.
CatVersion: Concatenating Embeddings for Diffusion-Based Text-to-Image Personalization
We propose CatVersion, an inversion-based method that learns the personalized concept through a handful of examples.
Adapt and Align to Improve Zero-Shot Sketch-Based Image Retrieval
Zero-shot sketch-based image retrieval (ZS-SBIR) is challenging due to the cross-domain nature of sketches and photos, as well as the semantic gap between seen and unseen image distributions.
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