I am a postdoctoral research scholar at Cornell-Tech, working with Professor Noah Snavely as part of the Cornell Graphics and Vision Group. My research interests are in computer graphics and vision, particularly in understanding visual concepts with little or no supervision.

I completed my PhD in the School of Electrical Engineering at Tel Aviv University. My PhD advisor is Professor Daniel Cohen-Or. I held various industrial research positions, most recently as a research scientist at Amazon. I received my B.Sc. in Electrical Engineering from the Technion (cum laude) in 2012.

Email: hadarelor [at] cornell.edu


Publications:

distilled Learning Gradient Fields for Shape Generation
Ruojin Cai, Guandao Yang, Hadar Averbuch-Elor, Zekun Hao, Serge Belongie, Noah Snavely, Bharath Hariharan
To appear in ECCV 2020, Spotlight
distilled Hidden Footprints: Learning Contextual Walkability from 3D Human Trails
Jin Sun, Hadar Averbuch-Elor, Qianqian Wang, Noah Snavely
To appear in ECCV 2020
distilled What is Learned in Visually Grounded Neural Syntax Acquisition
Noriyuki Kojima, Hadar Averbuch-Elor, Alexander Rush, Yoav Artzi
ACL 2020
[pdf]
distilled DualSDF: Semantic Shape Manipulation using a Two-Level Representation
Zekun Hao, Hadar Averbuch-Elor, Noah Snavely, Serge Belongie
CVPR 2020
[project page]
distilled ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation
Sharon Fogel, Hadar Averbuch-Elor, Sarel Cohen, Shai Mazor, Roee Litman
CVPR 2020
[pdf]
distilled READ: Recursive Autoencoders for Document Layout Generation
Akshay Gadi Patil, Omri Ben-Eliezer, Or Perel, Hadar Averbuch-Elor
CVPR Workshop on Text and Documents in Deep Learning Era 2020
Best Paper Award winner!
[pdf] [supp]
distilled Implicit Pairs for Boosting Unpaired Image-to-Image Translation
Yiftach Ginger, Dov Danon, Hadar Averbuch-Elor, Daniel Cohen-Or
Posted to Arxiv, 2019
[pdf]
distilled Border-Peeling Clustering
Hadar Averbuch-Elor, Nadav Bar, Daniel Cohen-Or
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2019
[pdf] [code]
distilled Clustering-driven Deep Embedding with Pairwise Constraints
Sharon Fogel, Hadar Averbuch-Elor, Jacob Goldberger, Daniel Cohen-Or
IEEE Computer Graphics and Applications 2019
[pdf]
distilled Unsupervised Natural Image Patch Learning
Dov Danon, Hadar Averbuch-Elor, Ohad Fried, Daniel Cohen-Or
Computational Visual Media 2019
Best Paper Award winner!
[pdf]
distilled Co-segmentation for Space-Time Co-located Collections
Hadar Averbuch-Elor, Johannes Kopf, Tamir Hazan, Daniel Cohen-Or
The Visual Computer 2018
[project page]
distilled Bringing Portraits to Life
Hadar Averbuch-Elor, Daniel Cohen-Or, Johannes Kopf, Michael F. Cohen
ACM Transactions on Graphics, Proc. SIGGRAPH Asia 2017
[project page]
distilled Smooth Image Sequences for Data-driven Morphing
Hadar Averbuch-Elor, Daniel Cohen-Or, Johannes Kopf
Eurographics 2016
[project page]
distilled Spherical Embedding of Inlier Silhouette Dissimilarities
Etai Littwin, Hadar Averbuch-Elor, Daniel Cohen-Or
CVPR 2015
[project page]
distilled Ring-It: Ring Ordering Casual Photos of a Temporal Event
Hadar Averbuch-Elor and Daniel Cohen-Or
ACM Transactions on Graphics 2015
[project page]
distilled Distilled Collections from Textual Image Queries
Hadar Averbuch-Elor, Yunhai Wang, Yiming Qian, Minglun Gong, Johannes Kopf, Hao Zhang and Daniel Cohen-Or
Eurographics 2015
[project page]