{"ID":2830425,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.10955","arxiv_id":"2512.10955","title":"Omni-Attribute: Open-vocabulary Attribute Encoder for Visual Concept Personalization","abstract":"Visual concept personalization aims to transfer only specific image attributes, such as identity, expression, lighting, and style, into unseen contexts. However, existing methods rely on holistic embeddings from general-purpose image encoders, which entangle multiple visual factors and make it difficult to isolate a single attribute. This often leads to information leakage and incoherent synthesis. To address this limitation, we introduce Omni-Attribute, the first open-vocabulary image attribute encoder designed to learn high-fidelity, attribute-specific representations. Our approach jointly designs the data and model: (i) we curate semantically linked image pairs annotated with positive and negative attributes to explicitly teach the encoder what to preserve or suppress; and (ii) we adopt a dual-objective training paradigm that balances generative fidelity with contrastive disentanglement. The resulting embeddings prove effective for open-vocabulary attribute retrieval, personalization, and compositional generation, achieving state-of-the-art performance across multiple benchmarks.","short_abstract":"Visual concept personalization aims to transfer only specific image attributes, such as identity, expression, lighting, and style, into unseen contexts. However, existing methods rely on holistic embeddings from general-purpose image encoders, which entangle multiple visual factors and make it difficult to isolate a si...","url_abs":"https://arxiv.org/abs/2512.10955","url_pdf":"https://arxiv.org/pdf/2512.10955v2","authors":"[\"Tsai-Shien Chen\",\"Aliaksandr Siarohin\",\"Gordon Guocheng Qian\",\"Kuan-Chieh Jackson Wang\",\"Egor Nemchinov\",\"Moayed Haji-Ali\",\"Riza Alp Guler\",\"Willi Menapace\",\"Ivan Skorokhodov\",\"Anil Kag\",\"Jun-Yan Zhu\",\"Sergey Tulyakov\"]","published":"2025-12-11T18:59:56Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false}