Abstract: A method and/or system for automated estimation of 3D orientation of a physical asset using deep learning models and computer vision algorithms, according to one or more embodiments. The system may be configured to receive images of the physical asset and camera orientation data as input, use deep learning neural network models to isolate the physical assets across the images, track each physical asset instance throughout the images and derive a 3D point cloud model of each asset by projecting binary masks of the asset contours from different view-points. The 3D point cloud model is further processed and supplemented with camera orientation data to estimate the 3D orientation of one or more assets present in the images.