Search Results for author: Afshin Dehghan

Found 12 papers, 4 papers with code

GAUDI: A Neural Architect for Immersive 3D Scene Generation

1 code implementation27 Jul 2022 Miguel Angel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, Josh Susskind

We introduce GAUDI, a generative model capable of capturing the distribution of complex and realistic 3D scenes that can be rendered immersively from a moving camera.

Image Generation Scene Generation

ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Data

1 code implementation17 Nov 2021 Gilad Baruch, Zhuoyuan Chen, Afshin Dehghan, Tal Dimry, Yuri Feigin, Peter Fu, Thomas Gebauer, Brandon Joffe, Daniel Kurz, Arik Schwartz, Elad Shulman

It is not only the first RGB-D dataset that is captured with a now widely available depth sensor, but to our best knowledge, it also is the largest indoor scene understanding data released.

3D Object Detection object-detection +1

DAGER: Deep Age, Gender and Emotion Recognition Using Convolutional Neural Network

2 code implementations14 Feb 2017 Afshin Dehghan, Enrique. G. Ortiz, Guang Shu, Syed Zain Masood

This paper describes the details of Sighthound's fully automated age, gender and emotion recognition system.

Emotion Recognition

View Independent Vehicle Make, Model and Color Recognition Using Convolutional Neural Network

1 code implementation6 Feb 2017 Afshin Dehghan, Syed Zain Masood, Guang Shu, Enrique. G. Ortiz

The backbone of our system is a deep convolutional neural network that is not only computationally inexpensive, but also provides state-of-the-art results on several competitive benchmarks.


Binary Quadratic Programing for Online Tracking of Hundreds of People in Extremely Crowded Scenes

no code implementations30 Mar 2016 Afshin Dehghan, Mubarak Shah

In this paper, we propose a tracker that addresses the aforementioned problems and is capable of tracking hundreds of people efficiently.

Multi-Object Tracking

Deep Tracking: Visual Tracking Using Deep Convolutional Networks

no code implementations13 Dec 2015 Meera Hahn, Si Chen, Afshin Dehghan

In this paper, we study a discriminatively trained deep convolutional network for the task of visual tracking.

Visual Tracking

Target Identity-Aware Network Flow for Online Multiple Target Tracking

no code implementations CVPR 2015 Afshin Dehghan, Yicong Tian, Philip H. S. Torr, Mubarak Shah

In this paper we show that multiple object tracking (MOT) can be formulated in a framework, where the detection and data-association are performed simultaneously.

Multiple Object Tracking object-detection +1

Improving Semantic Concept Detection through the Dictionary of Visually-distinct Elements

no code implementations CVPR 2014 Afshin Dehghan, Haroon Idrees, Mubarak Shah

A video captures a sequence and interactions of concepts that can be static, for instance, objects or scenes, or dynamic, such as actions.

Who Do I Look Like? Determining Parent-Offspring Resemblance via Gated Autoencoders

no code implementations CVPR 2014 Afshin Dehghan, Enrique. G. Ortiz, Ruben Villegas, Mubarak Shah

Recent years have seen a major push for face recognition technology due to the large expansion of image sharing on social networks.

Face Recognition

Improving an Object Detector and Extracting Regions Using Superpixels

no code implementations CVPR 2013 Guang Shu, Afshin Dehghan, Mubarak Shah

In general, our method takes detection bounding boxes of a generic detector as input and generates the detection output with higher average precision and precise object regions.


Cannot find the paper you are looking for? You can Submit a new open access paper.