activity
20172022
most citedEnd-to-end 3D shape inverse rendering of different classes of objects from a single input image

2 citations · 5 across the 4 of their papers we have counts for

collaborators

5 papers

cs.NE2019

A New Approach for Optimizing Highly Nonlinear Problems Based on the Observer Effect Concept

Mojtaba Moattari, Emad Roshandel, Shima Kamyab +1

A lot of real-world engineering problems represent dynamicity with nests of nonlinearities due to highly complex network of exponential functions or large number of differential eq…

cs.CV2019

Deep Generative Models: Deterministic Prediction with an Application in Inverse Rendering

Shima Kamyab, Rasool Sabzi, Zohreh Azimifar

Deep generative models are stochastic neural networks capable of learning the distribution of data so as to generate new samples. Conditional Variational Autoencoder (CVAE) is a po…

cs.CV2018

Unsupervised Feature Learning Toward a Real-time Vehicle Make and Model Recognition

Amir Nazemi, Mohammad Javad Shafiee, Zohreh Azimifar +1

Vehicle Make and Model Recognition (MMR) systems provide a fully automatic framework to recognize and classify different vehicle models. Several approaches have been proposed to ad…

cs.CV20172 cited

End-to-end 3D shape inverse rendering of different classes of objects from a single input image

Shima Kamyab, S. Zohreh Azimifar

In this paper a semi-supervised deep framework is proposed for the problem of 3D shape inverse rendering from a single 2D input image. The main structure of proposed framework cons…

cs.CV20172 cited

Deep Structure for end-to-end inverse rendering

Shima Kamyab, Ali Ghodsi, S. Zohreh Azimifar

Inverse rendering in a 3D format denoted to recovering the 3D properties of a scene given 2D input image(s) and is typically done using 3D Morphable Model (3DMM) based methods from…