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20152026
most citedUnsupervised Feature Learning Toward a Real-time Vehicle Make and Model Recognition

7 citations · 16 across the 10 of their papers we have counts for

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7 papers · 1 filter

cs.CV2025

Texture Image Synthesis Using Spatial GAN Based on Vision Transformers

Elahe Salari, Zohreh Azimifar

Texture synthesis is a fundamental task in computer vision, whose goal is to generate visually realistic and structurally coherent textures for a wide range of applications, from g…

cs.CV2022★ 1 cited

Deep-MDS Framework for Recovering the 3D Shape of 2D Landmarks from a Single Image

Shima Kamyab, Zohreh Azimifar

In this paper, a low parameter deep learning framework utilizing the Non-metric Multi-Dimensional scaling (NMDS) method, is proposed to recover the 3D shape of 2D landmarks on a hu…

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★ 7 cited

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.CV2017★ 2 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.CV2017★ 2 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…

cs.CV2015★ 4 cited

A Deep-structured Conditional Random Field Model for Object Silhouette Tracking

Mohammad Shafiee, Zohreh Azimifar, Alexander Wong

In this work, we introduce a deep-structured conditional random field (DS-CRF) model for the purpose of state-based object silhouette tracking. The proposed DS-CRF model consists o…