izadinia AT
Computer Science & Engr.
Paul G Allen Center
185 Stevens Way
Seattle, WA 98195-2350

I received PhD degree in Computer Science from University of Washington. I got advice from my PhD advisor Prof. Steve Seitz and my PhD committee Alexei Efros, Byron Boots and Brian Curless . I was also part of the Graphics-Vision Lab (GRAIL) at UW.

My research interest include 3D Deep Learning, Machine Learning, Deep Reinforcement Learning and 3D Scene Understanding.

Work Experience

Facebook Reality Labs (FRL)
Student Researcher
Redmond, WA
Fall 2017-Winter 2019
Research Intern, Oculus Research
San Francisco, CA
Summer 2017
Research Intern, Flickr
San Francisco, CA
Summer 2016
Research Intern, Adobe Research
(Creative Technologies Lab)
San Francisco, CA
Summer 2014
Research Intern, Disney Research
Pittsburgh, PA
Summer 2013
Visiting scholar, Robotics Institute
Carnegie Mellon University
Pittsburgh, PA
Summer 2012

selected publications (All publications)

Hamid Izadinia, Byron Boots, Steven M. Seitz
International Symposium on Experimental Robotics (ISER 2020).
Keywords: Riemannian Motion Policy (RMP), Nonprehensile manipulation, Model Predictive Control (MPC), Closed-Loop Control, Real-to-Sim reward analysis, RMPflow, real RC-car robot, fully automatic object-level scene recomposition, point cloud input, YCB dataset.
pdf · arXiv · project page
Hamid Izadinia, Steven M. Seitz
CVPR 2020.
A novel learning-based ICP and fully automatic Scene Recomposition that utilizes thousands of 3D CAD models to align 3D CAD to depth scan by Deep RL.
Keywords: 3D scene recomposition, 3D scene reconstruction, Deep reinforcement learning (Deep RL), Learning-based ICP (LICP), 3D geometry learning, 3D CAD models, 3D shapes, Room layout estimation, 3D geometry deep network, Iterative Closest Point, 3D geometry network, noisy scan.
pdf · arXiv · project page
Hamid Izadinia, Pierre Garrigues
CVPR 2020 - VL3.
A novel method to harness real adversarial examples from unlabeled images as a source of regularization data for learning robust visual representation.
Keywords: Visual self regularizers, approximate nearest neighbor, real adversarial example, adversarial regularization, regularization for training ConvNets, object-in-context retrieval and visual localization, semi-supervised and weakly-supervised deep learning, fully convolutional deep neural network, t-SNE embedding map, MS COCO and Visual Genome and YFCC100M dataset.
pdf · video · project page
Hamid Izadinia, Qi Shan, Steven M. Seitz
CVPR 2017. (spotlight)
Keywords: 3D scene reconstruction, convolutional neural network, reconstruction-recognition, scene optimization via render-and-match, single view geometry, room layout estimation, 3D CAD models.
pdf · arXiv · project page
Kofi Boakye, Sachin Farfade, Hamid Izadinia, Yannis Kalantidis, Pierre Garrigues
NeurIPS 2016 - Large Scale Computer Vision systems Workshop. (Best paper award)
Keywords: photo tagging, interpretable representation, deep convolutional neural networks, developing large-scale photo tagging system, lightweight and high-performance models, training noisy data.
H. Izadinia, F. Sadeghi, S.K. Divvala, Y. Choi, A. Farhadi
ICCV 2015. (oral)
Keywords: visual entailment, visual paraphrasing, semantic segmentation, large-scale recognition.
H. Izadinia, B. Russell, A. Farhadi, M. Hoffman, A. Hertzmann
Multimedia COMMONS, ACM Multimedia, 2015.
Keywords: deep learning, convolutional neural network, large-scale recognition, photo tagging, image classification, image retrieval, robust classification, deep tagging, YFCC100M (as noisy labeled dataset).
pdf  · Deep-Tagging demo
H. Izadinia*, F. Sadeghi*, A. Farhadi
CVPR, 2014.
Keywords: scene understanding, large-scale recognition, object layout inference, structured SVM, black-box test, scene context.
F. Sadeghi, H. Izadinia
preprint arXiv:1412.6079, December 2014.
Keywords: diagram understanding, visualization redesign, text visualization, computer vision, word cloud.
H. Izadinia, M. Shah
ECCV, 2012.
Keywords: complex event recognition, action recognition, structured learning, latent SVM.
H. Izadinia, I. Saleemi, W. Li, M. Shah
ECCV, 2012.
Keywords: multi-target, tracking, pedestrians, humans, body part tracking, network flow optimization, k-shortest paths.
H. Izadinia, I. Saleemi, M. Shah
Keywords: audio-visual analysis, canonical correlation analysis, video segmentation, audio-visual synchronization.
H. Izadinia, V. Ramakrishna, K. Kitani, D. Huber
WACV 2013.
Keywords: human pose estimation, multi-target tracking, action recognition.

Teaching GTA

Reinforcement Learning (RL), Q-Learning,
Value Iteration, Markov Decision Process (MDP),
CSP, Search, HMM, Bayesian Net, Perceptron.

Find the slides of our computer vision seminar class CSE590v (Autumn 2014)