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cs.CV2023
CREPE: Learnable Prompting With CLIP Improves Visual Relationship Prediction
Rakshith Subramanyam, T. S. Jayram, Rushil Anirudh +1
In this paper, we explore the potential of Vision-Language Models (VLMs), specifically CLIP, in predicting visual object relationships, which involves interpreting visual features…
cs.CV2023
Target-Aware Generative Augmentations for Single-Shot Adaptation
Kowshik Thopalli, Rakshith Subramanyam, Pavan Turaga +1
In this paper, we address the problem of adapting models from a source domain to a target domain, a task that has become increasingly important due to the brittle generalization of…