In IACV Lab, we work on various applications in Computer Vision and Machine Learning, one area being cross-modal matching. Due to increase in the number of sources of data, research in cross-modal matching is becoming an increasingly important area of research. It has several applications like matching text with image, matching near infra-red images with visible images for night-time or low-light surveillance, matching sketch images with pictures for forensic applications, etc. This is an extremely challenging task due to significant differences between data from different modalities. We have proposed several novel frameworks addressing the various challenges involved in this task.

Faculty: Soma Biswas

References:

T. Dutta, A. Singh, S. Biswas. StyleGuide: Zero-Shot Sketch-based Image Retrieval Using Style-Guided Image Generation. IEEE Transactions on Multimedia (TMM), 2021

S. Paul, T. Dutta, S. Biswas. Universal Cross-Domain Retrieval: Generalizing Across Classes and Domains, ICCV 2021.