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Found 4 papers, 0 papers with code
Making the V in Text-VQA Matter
Such a simple, yet effective approach increases the understanding and correlation between the image features and text present in the image, which helps in the better answering of questions.
Optical Character Recognition (OCR)
Visual Question Answering (VQA)
Weakly Supervised Visual Question Answer Generation
To address this issue, we propose a weakly-supervised visual question answer generation method that generates a relevant question-answer pairs for a given input image and associated caption.
Look, Read and Ask: Learning to Ask Questions by Reading Text in Images
However, it is challenging as it requires an in-depth understanding of the scene and the ability to semantically bridge the visual content with the text present in the image.
PIG-Net: Inception based Deep Learning Architecture for 3D Point Cloud Segmentation
In this paper, we address the problem of segmentation and labelling of the 3D point clouds by proposing a inception based deep network architecture called PIG-Net, that effectively characterizes the local and global geometric details of the point clouds.
