Toward Intelligent Scene Augmentation for Context-Aware Object Placement and Sponsor-Logo Integration
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866908731841708032 |
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| author | Saraswat, Unnati Rao, Tarun Gupta, Namah Swami, Shweta Sharma, Shikhar Narang, Prateek Kumar, Dhruv |
| author_facet | Saraswat, Unnati Rao, Tarun Gupta, Namah Swami, Shweta Sharma, Shikhar Narang, Prateek Kumar, Dhruv |
| contents | Intelligent image editing increasingly relies on advances in computer vision, multimodal reasoning, and generative modeling. While vision-language models (VLMs) and diffusion models enable guided visual manipulation, existing work rarely ensures that inserted objects are \emph{contextually appropriate}. We introduce two new tasks for advertising and digital media: (1) \emph{context-aware object insertion}, which requires predicting suitable object categories, generating them, and placing them plausibly within the scene; and (2) \emph{sponsor-product logo augmentation}, which involves detecting products and inserting correct brand logos, even when items are unbranded or incorrectly branded. To support these tasks, we build two new datasets with category annotations, placement regions, and sponsor-product labels. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_21560 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Toward Intelligent Scene Augmentation for Context-Aware Object Placement and Sponsor-Logo Integration Saraswat, Unnati Rao, Tarun Gupta, Namah Swami, Shweta Sharma, Shikhar Narang, Prateek Kumar, Dhruv Computer Vision and Pattern Recognition Intelligent image editing increasingly relies on advances in computer vision, multimodal reasoning, and generative modeling. While vision-language models (VLMs) and diffusion models enable guided visual manipulation, existing work rarely ensures that inserted objects are \emph{contextually appropriate}. We introduce two new tasks for advertising and digital media: (1) \emph{context-aware object insertion}, which requires predicting suitable object categories, generating them, and placing them plausibly within the scene; and (2) \emph{sponsor-product logo augmentation}, which involves detecting products and inserting correct brand logos, even when items are unbranded or incorrectly branded. To support these tasks, we build two new datasets with category annotations, placement regions, and sponsor-product labels. |
| title | Toward Intelligent Scene Augmentation for Context-Aware Object Placement and Sponsor-Logo Integration |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2512.21560 |