Robust 3D Reconstruction of Indoor Scenes using Deep Learning

Employing CNNs for an end-to-end reconstruction of the indoor scenes through camera relocalization, through PoseNet, and depth estimation, through multi-scale fully convolutional network, from a single RGB image during inference and registering the 3D reconstructed patches through iterative closest point algorithm. A portion of the dataset collected during the project is also released.

Graduate Student

My research interests include 3D vision, neural rendering, computer graphics, augmented and virtual reality.

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