Few-shot Learning with Noisy Labels
Kevin J Liang, Samrudhdhi B. Rangrej, Vladan Petrovic, Tal Hassner. Few-shot Learning with Noisy Labels. CVF/IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), New Orleans, LA, 2022.
Publications
Books
- Tal Hassner and Ce Liu (Eds.), Dense Image Correspondences for Computer Vision, Springer International Publishing, 2016 (Book at Springer)
Publications in Journals, Conferences and Workshops
Proactive Image Manipulation Detection
Vishal Asnani, Xi Yin, Tal Hassner, Sijia Liu, and Xiaoming Liu. Proactive Image Manipulation Detection. CVF/IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), New Orleans, LA, 2022.
FSGANv2: Improved Subject Agnostic Face Swapping and Reenactment
Yuval Nirkin, Yosi Keller, Tal Hassner, FSGANv2: Improved Subject Agnostic Face Swapping and Reenactment. IEEE Transactions on Pattern Analysis and Machine Intelligence. Accepted, March 2022.
Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection
Koby Bibas, Meir Feder, and Tal Hassner. Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection. Conference on Neural Information Processing Systems (NeurIPS), 2021.
DeepFake Detection Based on Discrepancies Between Faces and their Context
Yuval Nirkin, Lior Wolf, Yosi Keller and Tal Hassner, DeepFake Detection Based on Discrepancies Between Faces and their Context. IEEE Transactions on Pattern Analysis and Machine Intelligence. Accepted, June 2021
TextOCR: Towards large-scale end-to-end reasoning for arbitrary-shaped scene text
Amanpreet Singh, Guan Pang, Mandy Toh, Jing Huang, Wojciech Galuba, and Tal Hassner. TextOCR: Towards large-scale end-to-end reasoning for arbitrary-shaped scene text. CVF/IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, 2021.
A Multiplexed Network for End-to-End, Multilingual OCR
Jing Huang, Guan Pang, Rama Kovvuri, Mandy Toh, Kevin J Liang, Praveen Krishnan, Xi Yin, and Tal Hassner. A Multiplexed Network for End-to-End, Multilingual OCR. CVF/IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, 2021.
HyperSeg: Patch-wise Hypernetwork for Real-time Semantic Segmentation
Yuval Nirkin, Lior Wolf, Tal Hassner. HyperSeg: Patch-wise Hypernetwork for Real-time Semantic Segmentation. CVF/IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, 2021.
img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation
Vítor Albiero, Xingyu Chen, Xi Yin, Guan Pang, Tal Hassner. img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation. CVF/IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, 2021.
Mask TextSpotter v3: Segmentation Proposal Network for Robust Scene Text Spotting
Minghui Liao, Guan Pang, Jing Huang, Tal Hassner, and Xiang Bai. Mask TextSpotter v3: Segmentation Proposal Network for Robust Scene Text Spotting. European Conference on Computer Vision (ECCV), Glasgow, UK, 2020
LEEP: A New Measure to Evaluate Transferability of Learned Representations
Cuong V. Nguyen, Tal Hassner, Cedric Archambeau, Matthias Seeger. LEEP: A New Measure to Evaluate Transferability of Learned Representations. International Conference on Machine Learning (ICML), Vienna, Austria, 2020.
Meta-analysis of Continual Learning
Cuong V. Nguyen, Alessandro Achille, Michael Lam, Tal Hassner, Vijay Mahadevan, Stefano Soatto. Meta-analysis of Continual Learning. Conference on Neural Information Processing Systems (NeurIPS) workshops, Vancouver, CA, 2019.
FSGAN: Subject Agnostic Face Swapping and Reenactment
Yuval Nirkin, Yosi Keller, and Tal Hassner. FSGAN: Subject Agnostic Face Swapping and Reenactment. International Conference on Computer Vision (ICCV), Seoul, Korea, 2019.
Transferability and Hardness of Supervised Classification Tasks
Anh T. Tran, Cuong V. Nguyen, and Tal Hassner. Transferability and Hardness of Supervised Classification Tasks. International Conference on Computer Vision (ICCV), Seoul, Korea, 2019.
Face-Specific Data Augmentation for Unconstrained Face Recognition
Iacopo Masi, Anh Tuan Tran, Tal Hassner, Gozde Sahin, Gerard Medioni. Face-Specific Data Augmentation for Unconstrained Face Recognition. International Journal of Computer Vision (IJCV). 2019 Jun 1; 127(6-7):642-67
Deep, Landmark-Free FAME: Face Alignment, Modeling, and Expression Estimation
Feng-Ju Chang, Anh Tuan Tran, Tal Hassner, Iacopo Masi, Ram Nevatia, and Gerard Medioni. Deep, Landmark-Free FAME: Face Alignment, Modeling, and Expression Estimation. International Journal of Computer Vision (IJCV). 2019 Jun 1; 127(6-7):930-56
Balancing Specialization, Generalization, and Compression for Detection and Tracking
Dotan Kaufman, Koby Bibas, Eran Borenstein, Michael Chertok, and Tal Hassner. Balancing Specialization, Generalization, and Compression for Detection and Tracking. The British Machine Vision Conference (BMVC), Cardiff, UK, 2019.
Precise Detection in Densely Packed Scenes
Eran Goldman, Roei Herzig, Aviv Eisenschtat, Jacob Goldberger, Tal Hassner. Precise Detection in Densely Packed Scenes. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, 2019.
Learn Stereo, Infer Mono: Siamese Networks for Self-Supervised, Monocular, Depth Estimation
Matan Goldman, Tal Hassner, Shai Avidan. Learn Stereo, Infer Mono: Siamese Networks for Self-Supervised, Monocular, Depth Estimation. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) workshops, Long Beach, CA, 2019.
Fast and Accurate Line Detection with GPU-Based Least Median of Squares
Gil Shapira and Tal Hassner. Fast and Accurate Line Detection with GPU-Based Least Median of Squares. Journal of Real-Time Image Processing (RTIP), accepted.
Learning Pose-Aware Models for Pose-Invariant Face Recognition in the Wild
Iacopo Masi, Feng-ju Chang, Jongmoo Choi, Shai Harel, Jungyeon Kim, KangGeon Kim, Jatuporn Leksut, Stephen Rawls, Yue Wu, Tal Hassner*, Wael AbdAlmageed, Gerard Medioni, Louis-Philippe Morency, Prem Natarajan, Ram Nevatia. Learning Pose-Aware Models for Pose-Invariant Face Recognition in the Wild. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 41(2):379--393, Feb. 2019.
* Denotes first / lead senior author.
Paper at IEEE Xplore
Facial Landmark Detection with Tweaked Convolutional Neural Networks
Yue Wu*, Tal Hassner*, KangGeon Kim, Gerard Medioni, and Prem Natarajan. Facial Landmark Detection with Tweaked Convolutional Neural Networks. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 40(12):3067--3074, Dec. 2018.
* Denotes joint first authorship / equal contribution.
Old arXiv preprint and Paper on IEEE Xplore
Deep Face Recognition: a Survey
I. Masi, Y. Wu, T. Hassner, P. Natarajan, Deep Face Recognition: a Survey, Conference on Graphics, Patterns and Images (SIBGRAPI), Parana, Brazil, October 2018
CNN Prediction of Future Disease Activity for Multiple Sclerosis Patients from Baseline MRI and Lesion Labels
N. Mohammadi-Sepahvand, T. Hassner, D.L. Arnold and T. Arbel, CNN Prediction of Future Disease Activity for Multiple Sclerosis Patients from Baseline MRI and Lesion Labels, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) Workshops, Grenada, Spain, September 2018
Extreme 3D Face Reconstruction: Seeing through Occlusions
Anh Tuan Tran, Tal Hassner, Iacopo Masi, Eran Paz, Yuval Nirkin, Gerard Medioni. Extreme 3D Face Reconstruction: Seeing through Occlusions. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, 2018.
On Face Segmentation, Face Swapping, and Face Perception
Yuval Nirkin, Iacopo Masi, Anh Tuan Tran, Tal Hassner, and Gerard Medioni. On Face Segmentation, Face Swapping, and Face Perception. IEEE Conference on Automatic Face and Gesture Recognition (FG), Xi'an, China, 2018.
ExpNet: Landmark-Free, Deep, 3D Facial Expressions
FengJu Chang, Anh Tuan Tran, Tal Hassner, Iacopo Masi, Ram Nevatia, Gerard Medioni. ExpNet: Landmark-Free, Deep, 3D Facial Expressions. IEEE Conference on Automatic Face and Gesture Recognition (FG), Xi'an, China, 2018.
Temporal Tessellation: A Unified Approach for Video Analysis
Dotan Kaufman, Gil Levi, Tal Hassner, and Lior Wolf. Temporal Tessellation: A Unified Approach for Video Analysis. International Conference on Computer Vision (ICCV), Venice, Italy, 2017.
FacePoseNet: Making a Case for Landmark-Free Face Alignment
FengJu Chang, Anh Tuan Tran, Tal Hassner, Iacopo Masi, Ram Nevatia, Gerard Medioni. FacePoseNet: Making a Case for Landmark-Free Face Alignment. IEEE Workshop on Analysis and Modeling of Faces and Gestures (AMFG), at the IEEE Int. Conf. on Computer Vision (ICCV), Venice, Italy, 2017.
Accurate 3D Face Reconstruction via Prior Constrained Structure From Motion
Matthias Hernandez, Tal Hassner, Jongmoo Choi, and Gerard Medioni. Accurate 3D face reconstruction via prior constrained structure from motion. Computers & Graphics (CAG), 66: 14-22, 2017.
SIFTing Through Scales
Tal Hassner, Shay Filosof, Viki Mayzels, and Lihi Zelnik-Manor. SIFTing through Scales. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 39(7): 1431-1443, 2017.
Regressing Robust and Discriminative 3D Morphable Models With a Very Deep Neural Network
Anh Tuan Tran, Tal Hassner, Iacopo Masi, and Gerard Medioni. Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Honolulu, 2017.
Rapid Synthesis of Massive Face Sets for Improved Face Recognition
Iacopo Masi, Tal Hassner, Anh Tuan Tran, and Gerard Medioni. Rapid Synthesis of Massive Face Sets for Improved Face Recognition. IEEE International Conference on Automatic Face and Gesture Recognition (FG) Washington, DC, 2017.
Do We Really Need to Collect Millions of Faces for Effective Face Recognition?
Iacopo Masi*, Anh Tuan Tran*, Tal Hassner*, Jatuporn Toy Leksut and Gerard Medioni. Do We Really Need to Collect Millions of Faces for Effective Face Recognition? European Conference on Computer Vision (ECCV), Amsterdam, The Netherlands, 2016.
* Denotes equal contribution.
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The CUDA LATCH Binary Descriptor: Because Sometimes Faster Means Better
Christopher Parker, Matthew Daiter, Kareem Omar, Gil Levi and Tal Hassner. The CUDA LATCH Binary Descriptor: Because Sometimes Faster Means Better. Workshop on Local Features: State of the art, open problems and performance evaluation, at the European Conference on Computer Vision (ECCV), Amsterdam, The Netherlands, 2016.
Pooling Faces: Template Based Face Recognition with Pooled Face Images
Tal Hassner, Iacopo Masi, Jungyeon Kim, Jongmoo Choi, Shai Harel, Prem Natarajan, Gerard Medioni (2016). "Pooling Faces: Template based Face Recognition with Pooled Face Images." IEEE Computer Society Workshop on Biometrics at the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR).
Dense Correspondences Across Scenes and Scales
Moria Tau and Tal Hassner. Dense Correspondences across Scenes and Scales. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 38(5): 875-888, 2016.
Automated Detection of Feeding Strikes by Larval Fish Using Continuous High-Speed Digital Video: a Novel Method to Extract Quantitative Data From Fast, Sparse Kinematic Events
Eyal Shamur, Miri Zilka, Tal Hassner, Victor China, Alex Liberzon, and Roi Holzman. Automated detection of feeding strikes by larval fish using continuous high-speed digital video: a novel method to extract quantitative data from fast, sparse kinematic events. Journal of Experimental Biology (JEB), volume 219, number 11, pp. 1608--1617, 2016.
LATCH: Learned Arrangements of Three Patch Codes
Gil Levi and Tal Hassner. LATCH: Learned Arrangements of Three Patch Codes. IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Placid, NY, USA, 2016.
Texture Instance Similarity via Dense Correspondences
Tal Hassner, Gilad Saban and Lior Wolf. Texture Instance Similarity via Dense Correspondences. IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Placid, NY, USA, 2016.
Face Recognition Using Deep Multi-Pose Representations
Wael AbdAlmageed, Yue Wu, Stephen Rawls, Shai Harel, Tal Hassner, Iacopo Masi, Jongmoo Choi, Jatuporn Lekust, Jungyeon Kim, Prem Natarajan, Ram Nevatia and Gerard Medioni. (2016). "Face Recognition Using Deep Multi-Pose Representations." IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Placid, NY, USA.
Wide Baseline Stereo Matching With Convex Bounded-Distortion Constraints
Meirav Galun*, Tal Amir*, Tal Hassner, Ronen Basri, and Yaron Lipman. Wide baseline stereo matching with convex bounded-distortion constraints. International Conference on Computer Vision (ICCV), Santiago, Chile, 2015.
* Denotes equal contribution.
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Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns
Gil Levi and Tal Hassner. Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns. Proc. ACM International Conference on Multimodal Interaction (ICMI), Seattle, 2015.
Viral Transcription Alignment
Gil Sadeh, Lior Wolf, Tal Hassner, Nachum Dershowitz, and Daniel Stokl Ben-Ezra. Viral Transcription Alignment. International Conference on Document Analysis and Recognition (ICDAR), Nancy, France, 2015.
Effective Face Frontalization in Unconstrained Images
Tal Hassner, Shai Harel*, Eran Paz* and Roee Enbar. Effective Face Frontalization in Unconstrained Images. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Boston, 2015.
* These author names are in alphabetical order due to equal contribution.
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Age and Gender Classification Using Convolutional Neural Networks
Gil Levi and Tal Hassner.Age and Gender Classification Using Convolutional Neural Networks. IEEE Workshop on Analysis and Modeling of Faces and Gestures (AMFG), at the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Boston, 2015.
Teaching Computer Vision: Bringing Research Benchmarks to the Classroom
Tal Hassner and Itzik Bayaz. Teaching Computer Vision: Bringing Research Benchmarks to the Classroom. ACM Transactions on Computing Education (ACM-TOCE), Volume 14 Issue 4, 2015.
Age and Gender Estimation of Unfiltered Faces
Eran Eidinger, Roee Enbar, Tal Hassner. Age and Gender Estimation of Unfiltered Faces. Transactions on Information Forensics and Security (IEEE-TIFS), special issue on Facial Biometrics in the Wild, Volume 9, Issue 12, pages 2170 - 2179, 2014.
R. Enbar selected for the 2017 SPS Young Author Best Paper Award by the IEEE Signal Processing Society.
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A Piggyback Representation for Action Recognition
Lior Wolf, Yair Hanani, Tal Hassner. A Piggyback Representation for Action Recognition. IEEE International Workshop on Deep-Vision, at the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, 2014
When Standard RANSAC is Not Enough: Cross-Media Visual Matching with Hypothesis Relevancy
Tal Hassner, Liav Assif, Lior Wolf. When Standard RANSAC is Not Enough: Cross-Media Visual Matching with Hypothesis Relevancy. Machine Vision and Applications (MVAP), Volume 25, Issue 4, Page 971-983, 2014.
Viewing Real-World Faces in 3D
Tal Hassner. Viewing Real-World Faces in 3D. International Conference on Computer Vision (ICCV), Sydney, Austraila, 2013.
Interactive Learning for Point-Cloud Motion Segmentation
Yerry Sofer, Tal Hassner, and Andrei Sharf. Interactive Learning for Point-Cloud Motion Segmentation. Computer Graphics Forum, vol. 32, no. 7, pp. 51-60, 2013.
OCR-Free Transcript Alignment
Tal Hassner, Lior Wolf, and Nachum Dershowitz. OCR-Free Transcript Alignment. International Conference on Document Analysis and Recognition (ICDAR), Washington DC, 2013.
A Critical Review of Action Recognition Benchmarks
Tal Hassner. A Critical Review of Action Recognition Benchmarks. 1st IEEE International Workshop on Action Similarity in Unconstrained Videos (ACTS) at the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Portland, Oregon, 2013
Motion Interchange Patterns for Action Recognition in Unconstrained Videos
Orit Kliper-Gross, Yaron Gurovich, Tal Hassner.Motion Interchange Patterns for Action Recognition in Unconstrained Videos. European Conference on Computer Vision (ECCV), Firenze , Italy, 2012.
Computation and Palaeography: Potentials and Limits (Dagstuhl Perspectives Workshop 12382)
Tal Hassner, Malte Rehbein, Peter A. Stokes, and Lior Wolf. Computation and Palaeography: Potentials and Limits (Dagstuhl Perspectives Workshop 12382). Dagstuhl Manifestos 2(1): 14-35, 2012.
On SIFTs and Their Scales
Tal Hassner, Viki Mayzels, and Lihi Zelnik-Manor. On SIFTs and their Scales. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Rhode Island, 2012.
Violent Flows: Real-Time Detection of Violent Crowd Behavior
Tal Hassner, Yossi. Itcher, and Orit Kliper-Gross. Violent Flows: Real-Time Detection of Violent Crowd Behavior. 3rd IEEE International Workshop on Socially Intelligent Surveillance and Monitoring (SISM) at the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Rhode Island, 2012.
Viewing the Viewers: How Adults With Attentional Deficits Watch Educational Videos
Tal Hassner, Lior Wolf, Anat Lerner, and Yael Leitner. Viewing the Viewers: How Adults With Attentional Deficits Watch Educational Videos. SAGE Journal of Attention Disorders (JAD), October 2014 vol. 18 no. 7, pp. 585-593
Originally published ahead of print, May 24th, 2012 (Paper at SAGE)
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Press coverage:
- August 2012: Feature article in the popular-science magazine ‘Galileo’, issue 168, in Hebrew.
- Summer 2012: Feature article in Open Letter, The Open University of Israel magazine. Available online.
- 18th of July, 2012: Radio interview on ‘Hakol Tsafui’, Reshet-Aleph, in Hebrew.
- 9th of July, 2012: Maariv (One of the two largest daily newspapers in Israel), in Hebrew.
- 9th of July, 2012: Radio interview on Yael Dan’s show, Galey Zahal, in Hebrew.
- 1st of July, 2012: Dudi Goldman radio interview on the ‘Economic Show’, Galey Zahal, in Hebrew.
The Action Similarity Labeling Challenge
Orit Kliper-Gross, Tal Hassner, and Lior Wolf. The Action Similarity Labeling Challenge. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 34(3), 2012
Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics
Lior Wolf, Tal Hassner, and Yaniv Taigman. Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 33(10), 2011.
Press coverage:
Winter 2011 - Feature article in Open Letter, The Open University of Israel Magazine. Available online.
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One Shot Similarity Metric Learning for Action Recognition
Orit Kliper-Gross, Tal Hassner, and Lior Wolf. One Shot Similarity Metric Learning for Action Recognition. International Workshop on Similarity-Based Pattern Analysis and Recognition (SIMBAD), Venice, Italy, 2011.
Face Recognition in Unconstrained Videos with Matched Background Similarity
Lior Wolf, Tal Hassner, and Itay Maoz. Face Recognition in Unconstrained Videos with Matched Background Similarity. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, 2011.
Approximate Nearest Subspace Search
Ronen Basri, Tal Hassner, and Lihi Zelnik-Manor*. Approximate Nearest Subspace Search; IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 33(2), 2011
Editor’s selection for spotlight paper
* Author names in alphabetical order due to equal contribution.
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Variational Relevance Vector Machine for Tabular Data
Dmitry Kropotov, Dmitry Vetrov, Lior Wolf, and Tal Hassner. Variational Relevance Vector Machine for Tabular Data. JMLR: Workshop and Conference Proceedings 13: 79-94, Asian Conference on Machine Learning (ACML), Tokyo, 2010.
A General Framework for Approximate Nearest Subspace Search
Ronen Basri, Tal Hassner, and Lihi Zelnik-Manor*. A General Framework for Approximate Nearest Subspace Search. 2nd IEEE International Workshop on Subspace Methods at the IEEE International Conference on Computer Vision (ICCV), Kyoto, 2009.
* Author names in alphabetical order due to equal contribution.
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The One-Shot Similarity Kernel
Lior Wolf, Tal Hassner, and Yaniv Taigman. The One-Shot Similarity Kernel. IEEE International Conference on Computer Vision (ICCV), Kyoto, 2009.
Multiple One-Shots for Utilizing Class Label Information
Yaniv Taigman, Lior Wolf, and Tal Hassner. Multiple One-Shots for Utilizing Class Label Information. The British Machine Vision Conference (BMVC), London, 2009.
Similarity Scores Based on Background Samples
Lior Wolf, Tal Hassner, and Yaniv Taigman. Similarity Scores based on Background Samples. Asian Conference on Computer Vision (ACCV), Xi'an, 2009.
Descriptor Based Methods in the Wild
Lior Wolf, Tal Hassner, and Yaniv Taigman. Descriptor Based Methods in the Wild. Faces in Real-Life Images workshop at the European Conference on Computer Vision (ECCV), Marseille, 2008.
Best result on the “LFW face recognition benchmark”, at the Faces in Real-Life Images workshop, 2008.
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Surface Reconstruction using Local Shape Priors
Ran Gal, Ariel Shamir, Tal Hassner, Mark Pauly and Daniel Cohen-Or. Surface Reconstruction using Local Shape Priors. Proceedings of the fifth Eurographics Symposium on Geometry Processing (SGP), Barcelona, 2007.
Approximate Nearest Subspace Search with Applications to Pattern Recognition
Ronen Basri, Tal Hassner, and Lihi Zelnik-Manor*. Approximate Nearest Subspace Search with Applications to Pattern Recognition. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Minneapolis, 2007.
* Author names in alphabetical order due to equal contribution
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Automatic Depth-Map Colorization
Tal Hassner and Ronen Basri. Automatic Depth-Map Colorization, Eurographics (short), Vienna, 2006.
Patent pending.
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Example Based 3D Reconstruction from Single 2D Images
Tal Hassner and Ronen Basri. Example Based 3D Reconstruction from Single 2D Images, Beyond Patches Workshop at IEEE Conference on Computer Vision and Pattern Recognition (CVPR), New-York, 2006.
Patent pending.
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Minimal-Cut Model Composition
Tal Hassner, Lihi Zelnik-Manor, George Leifman, and Ronen Basri. Minimal-Cut Model Composition, International Conference on Shape Modeling and Applications (SMI), Boston, 2005
Best Student Paper Award at SMI 2005; Patent pending.
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What Does the Scene Look Like from a Scene Point?
Michal Irani, Tal Hassner, and P.Anandan. What Does the Scene Look Like from a Scene Point? European Conference on Computer Vision (ECCV), 2002
Press coverage:
2004, TV Interivew on Channel 8, “The Science Channel”, on the “Science News” show, in Hebrew.
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Reports
Cuong V. Nguyen, Alessandro Achille, Michael Lam, Tal Hassner, Vijay, Mahadevan, Stefano Soatto, Toward Understanding Catastrophic Forgetting in Continual Learning, arXiv preprint arXiv:1908.01091, 2 Aug 2019, (arXiv)
Tal Hassner, Malte Rehbein, Peter A. Stokes, and Lior Wolf, Computation and Palaeography: Potentials and Limits (Dagstuhl Perspectives Workshop 12382). Dagstuhl Reports 2(9): 184-199 (2012) (info, PDF)
Tal Hassner and Ronen Basri, Single View Depth Estimation from Examples, arXiv preprint arXiv:1304.3915, 14 Apr 2013 (arXiv)
Ronen Basri, Tal Hassner and Lihi Zelnik-Manor, A General Framework for Approximate Nearest Subspace Search, Technical Report CCIT #699, Department of Electrical Engineering, Technion, June 2008. (PDF)
* Author names in alphabetical order due to equal contribution.Tal Hassner, Building 3D Shapes from Parts, Ph.D. Thesis, Faculty of Mathematics and Computer Science, The Weizmann Institute of Science, December, 2006.
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