Towards Efficient Exemplar Based Image Editing with Multimodal VLMs

• URL: http://arxiv.org/abs/2506.20155v1
• Date: Wed, 25 Jun 2025 06:20:36 GMT
• Title: Towards Efficient Exemplar Based Image Editing with Multimodal VLMs
• Authors: Avadhoot Jadhav, Ashutosh Srivastava, Abhinav Java, Silky Singh, Tarun Ram Menta, Surgan Jandial, Balaji Krishnamurthy,
• Abstract summary: In this work, we tackle the task of transferring an edit from an exemplar pair to a content image(s) by leveraging text-to-image diffusion models and multimodal VLMs.<n>Our end-to-end pipeline is optimization-free, but our experiments demonstrate that it still outperforms baselines on multiple types of edits while being 4x faster.
• Score: 11.830273909934688
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Text-to-Image Diffusion models have enabled a wide array of image editing applications. However, capturing all types of edits through text alone can be challenging and cumbersome. The ambiguous nature of certain image edits is better expressed through an exemplar pair, i.e., a pair of images depicting an image before and after an edit respectively. In this work, we tackle exemplar-based image editing -- the task of transferring an edit from an exemplar pair to a content image(s), by leveraging pretrained text-to-image diffusion models and multimodal VLMs. Even though our end-to-end pipeline is optimization-free, our experiments demonstrate that it still outperforms baselines on multiple types of edits while being ~4x faster.

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