Sandwich Degree in Mechatronic Engineering from the Federal University of Uberlândia (Brazil) and ENSMM (France). She completed her course completion project in Robotics guided by Computer Vision.Visiting Researcher with BEPE FAPESP scholarship at the University of Oslo, Norway. His paper was accepted into the ICCV2023 Vision-and-Language Algorithm Reasoning Workshop, winning the Math Kangaroo Best Paper Award.Currently a PhD student at Unicamp in Computer Science with a focus on Causality in AI, Information Engineering. (Source: Lattes Curriculum)
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Visual Question Answering (VQA) is a task that aims to answer a user's question grounded to a given image. Normally, this task requires a combination of concepts from Computer Vision and Natural Language Processing. The majority of existing VQA systems merge the extracted image and question features in order to predict an answer. Nonetheless, this multi-modal fusion shows a significant ga…
Visual question answering (VQA) is an attractive multi-model research field aiming to answer a free-form question based on an image. Its attractiveness lies in the fact that it combines two fields that are typically approached individually, computer vision (CV) and natural language processing (NLP). In order to achieve a comprehensive and semantically alignment between the two fields, som…
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