Toward Intelligent Scene Augmentation for Context-Aware Object Placement and Sponsor-Logo Integration
This work addresses the need for more intelligent image editing tools in advertising and digital media, though it is incremental as it builds on existing vision-language and diffusion models.
The paper tackles the problem of ensuring contextually appropriate object insertion in images by introducing two new tasks for advertising and digital media: context-aware object insertion and sponsor-product logo augmentation, and builds two new datasets to support these tasks.
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.