Xinliang Zhu

Jul 3, 2024 | amazon.science | Xinliang Zhu |Michael Huang |Jinyu Yang |Kelvin Chen

Image to image matching has been well studied in the computer vision community. Previous studies mainly focus on training a deep metric learning model matching visual patterns between the query image and gallery images. In this study, we show that pure image-to-image matching suffers from false positives caused by matching to local visual patterns. To alleviate this issue, we propose to leverage recent advances in vision-language pretraining research.

Apr 16, 2024 | amazon.science | Michael Huang |Xinliang Zhu |Arnab Dhua |Oriol Barbany Mayor

Multimodal search has become increasingly important in providing users with a natural and effective way to ex-press their search intentions. Images offer fine-grained details of the desired products, while text allows for easily incorporating search modifications. However, some existing multimodal search systems are unreliable and fail to address simple queries.