Computer Vision News 8 Congrats, Doctor Carlos! Carlos Rodríguez - Pardo did an industrial PhD at Universidad Rey Juan Carlos, which was fully funded by SEDDI, a startup based in Madrid focused on digitizing the fashion industry. His PhD was supervised by awesome Elena Garcés. The focus of his thesis is to develop deep learning based methods for digitizing materials, inverse graphics, and encoding radiance for virtual scenes. Congrats, Doctor Carlos! Realistic virtual scenes are becoming increasingly prevalent in our society, with a wide range of applications in areas such as manufacturing, architecture, fashion design, and entertainment, including movies, video games, and augmented and virtual reality. Generating realistic images of such scenes requires highly accurate illumination, geometry, and material models, which can be time-consuming and challenging to obtain. Traditionally, such models have often been created manually by skilled artists, but this process can be prohibitively time-consuming and costly. Alternatively, real-world examples can be captured, but this approach presents additional challenges in terms of accuracy and scalability. Moreover, while realism and accuracy are crucial in such processes, rendering efficiency is also a key requirement, so that lifelike images can be generated with the speed required in many real-world applications. One of the most significant challenges in this regard is the acquisition and representation of materials, which are a critical component of our visual world and, by extension, of virtual representations of it. However, existing approaches for material acquisition and representation are limited in terms of efficiency and accuracy, which limits their real-world impact. To address Neural Networks for Digital Materials and Radiance Encoding Carlos with Elena at CVPR
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