User-Instructed Disparity-aware Defocus Control
–Neural Information Processing Systems
In photography, an All-in-Focus (AiF) image may not always effectively convey the creator's intent. Professional photographers manipulate Depth of Field (DoF) to control which regions appear sharp or blurred, achieving compelling artistic effects. For general users, the ability to flexibly adjust DoF enhances creative expression and image quality. In this paper, we propose UiD, a User-Instructed DoF control framework, that allows users to specify refocusing regions using text, box, or point prompts, and our UiD automatically simulates in-focus and out-of-focus (OoF) regions in the given images. However, controlling defocus blur in a single-lens camera remains challenging due to the difficulty in estimating depth-aware aberrations and the suboptimal quality of reconstructed AiF images.
Neural Information Processing Systems
Jun-15-2026, 04:24:56 GMT
- Country:
- Europe (1.00)
- Asia (0.68)
- North America > United States
- California (0.67)
- Genre:
- Research Report > Experimental Study (1.00)
- Industry:
- Media > Photography (1.00)
- Technology:
- Information Technology
- Sensing and Signal Processing > Image Processing (1.00)
- Communications (1.00)
- Data Science (0.67)
- Artificial Intelligence
- Vision (1.00)
- Natural Language (1.00)
- Representation & Reasoning (0.93)
- Machine Learning
- Statistical Learning (1.00)
- Neural Networks (1.00)
- Information Technology