Gerberth Adín Ramírez Rivera in research grants and scholarships supported by FAPESP.
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Automatic media generation (or synthesis) is a field that had an incredible boost in recent years, with the advent of deep generative models. Nowadays, neural networks can create text, images and videos based on class labels or other media. The common task is to generate content. However, we can take advantage of the learned feature representations on these tasks to understand the releva…
The number of smart devices and personal electronic equipments that we own and interact with is increasing every day. Given that facial expressions and corporal language are the most emotion-related signals humans emit, it is natural to incorporate human expression recognition capabilities into smart devices to improve their functionalities. Furthermore, human expression recognition techn…
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…
Semantic segmentation is one of the great open-ended problems in computer vision. This problem consists in classifying each pixel present in an image, delimiting an object. Convolutional neural networks have been shown to be efficient in detecting, identifying and segmenting objects in images. However, during the segmentation process, some problems arise, such as loss of spatial informati…
An important property of human perception is that one does not tend to process a whole scene in its entirety at once, for example, if we want to tell which model is a car, we do not need to look at people or animals in the environment. Likewise, when doing classification in pictures, we need to “pay attention” in certain parts of the image. Attention is an important component of neural ne…
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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…
Semantic segmentation task aims to create a dense classification by labeling pixel-wise each object present in images or videos. Convolutional neural network (CNN) approaches have been proved useful by exhibiting the best results in this task. Some challenges remain, however, such as the low-resolution of feature maps and the loss of spatial precision, both produced in the CNNs by limited…
| 3 / 3 | Completed research grants |
| 5 / 5 | Completed scholarships in Brazil |
| 1 / 1 | Ongoing scholarships abroad |
| 1 / 1 | Completed scholarships abroad |
| 10 / 10 | All research grants and scholarships |
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