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ORCIDErik G. Learned-Miller
Erik Gundersen Miller – Erik G. Miller
Person information
- affiliation: University of Massachusetts Amherst, USA
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Books and Theses
- 2002
[b1]Erik Gundersen Miller:
Learning from one example in machine vision by sharing probability densities. Massachusetts Institute of Technology, Cambridge, MA, USA, 2002
Journal Articles
- 2024
- [j18]Pia Bideau
, Erik G. Learned-Miller, Cordelia Schmid, Karteek Alahari:
The Right Spin: Learning Object Motion from Rotation-Compensated Flow Fields. Int. J. Comput. Vis. 132(1): 40-55 (2024) - 2023
- [j17]Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha:
A domain-agnostic approach for characterization of lifelong learning systems. Neural Networks 160: 274-296 (2023) - 2022
- [j16]Gopal Sharma, Bidya Dash, Aruni Roy Chowdhury, Matheus Gadelha, Marios Loizou, Liangliang Cao, Rui Wang, Erik G. Learned-Miller, Subhransu Maji, Evangelos Kalogerakis:
PriFit: Learning to Fit Primitives Improves Few Shot Point Cloud Segmentation. Comput. Graph. Forum 41(5): 39-50 (2022) - 2021
- [j15]Alireza Sedghi, Lauren J. O'Donnell, Tina Kapur, Erik G. Learned-Miller, Parvin Mousavi, William M. Wells III:
Image registration: Maximum likelihood, minimum entropy and deep learning. Medical Image Anal. 69: 101939 (2021) - 2019
- [j14]Keen Sung, Joydeep Biswas, Erik G. Learned-Miller, Brian Neil Levine, Marc Liberatore:
Server-Side Traffic Analysis Reveals Mobile Location Information over the Internet. IEEE Trans. Mob. Comput. 18(6): 1407-1418 (2019) - 2017
- [j13]Kristen Grauman, Erik G. Learned-Miller, Antonio Torralba, Andrew Zisserman:
Guest Editorial: Best of CVPR 2015. IEEE Trans. Pattern Anal. Mach. Intell. 39(4): 625-626 (2017) - 2014
- [j12]Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller:
Background subtraction: separating the modeling and the inference. Mach. Vis. Appl. 25(5): 1163-1174 (2014) - 2013
- [j11]Mastooreh Salajegheh, Yue Wang, Anxiao Jiang, Erik G. Learned-Miller, Kevin Fu:
Half-Wits: Software Techniques for Low-Voltage Probabilistic Storage on Microcontrollers with NOR Flash Memory. ACM Trans. Embed. Comput. Syst. 12(2s): 91:1-91:25 (2013) - 2012
- [j10]Gary B. Huang, Andrew Kae, Carl Doersch, Erik G. Learned-Miller:
Bounding the Probability of Error for High Precision Optical Character Recognition. J. Mach. Learn. Res. 13: 363-387 (2012) - 2011
- [j9]Andrew Kae, David A. Smith, Erik G. Learned-Miller:
Learning on the fly: a font-free approach toward multilingual OCR. Int. J. Document Anal. Recognit. 14(3): 289-301 (2011) - [j8]Gang Hua, Ming-Hsuan Yang, Erik G. Learned-Miller, Yi Ma, Matthew A. Turk, David J. Kriegman, Thomas S. Huang:
Introduction to the Special Section on Real-World Face Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 33(10): 1921-1924 (2011) - 2009
- [j7]Jerod J. Weinman, Erik G. Learned-Miller, Allen R. Hanson:
Scene Text Recognition Using Similarity and a Lexicon with Sparse Belief Propagation. IEEE Trans. Pattern Anal. Mach. Intell. 31(10): 1733-1746 (2009) - 2008
- [j6]Andras Ferencz, Erik G. Learned-Miller, Jitendra Malik:
Learning to Locate Informative Features for Visual Identification. Int. J. Comput. Vis. 77(1-3): 3-24 (2008) - [j5]Erik G. Learned-Miller, Joseph DeStefano:
A Probabilistic Upper Bound on Differential Entropy. IEEE Trans. Inf. Theory 54(11): 5223-5230 (2008) - 2007
- [j4]Manjunatha Jagalur, Chris Pal, Erik G. Learned-Miller, R. Thomas Zoeller, David Kulp:
Analyzing in situ gene expression in the mouse brain with image registration, feature extraction and block clustering. BMC Bioinform. 8(S-10) (2007) - 2006
- [j3]Erik G. Learned-Miller:
Data Driven Image Models through Continuous Joint Alignment. IEEE Trans. Pattern Anal. Mach. Intell. 28(2): 236-250 (2006) - 2003
- [j2]Erik G. Learned-Miller, John W. Fisher III:
ICA Using Spacings Estimates of Entropy. J. Mach. Learn. Res. 4: 1271-1295 (2003) - 1999
- [j1]Erik G. Miller:
Alternative Tilings for Improved Surface Area Estimates by Local Counting Algorithms. Comput. Vis. Image Underst. 74(3): 193-211 (1999)
Conference and Workshop Papers
- 2023
- [c98]Zitian Chen, Yikang Shen, Mingyu Ding, Zhenfang Chen, Hengshuang Zhao, Erik G. Learned-Miller, Chuang Gan:
Mod-Squad: Designing Mixtures of Experts As Modular Multi-Task Learners. CVPR 2023: 11828-11837 - [c97]Ashish Singh, Michael J. Jones, Erik G. Learned-Miller:
EVAL: Explainable Video Anomaly Localization. CVPR 2023: 18717-18726 - [c96]Ashutosh Singh, Ashish Singh, Aria Masoomi, Tales Imbiriba, Erik G. Learned-Miller, Deniz Erdogmus:
Inv-Senet: Invariant Self Expression Network for Clustering Under Biased Data. ICASSP 2023: 1-5 - [c95]Fabien Delattre, David Dirnfeld, Phat Nguyen, Stephen Scarano, Michael J. Jones, Pedro Miraldo, Erik G. Learned-Miller:
Robust Frame-to-Frame Camera Rotation Estimation in Crowded Scenes. ICCV 2023: 9718-9728 - [c94]Shifan Zhu, Zhipeng Tang, Michael Yang, Erik G. Learned-Miller, Donghyun Kim:
Event Camera-Based Visual Odometry for Dynamic Motion Tracking of a Legged Robot Using Adaptive Time Surface. IROS 2023: 3475-3482 - [c93]Ke Xiao, Erik G. Learned-Miller, Evangelos Kalogerakis, James Priest, Madalina Fiterau:
Machine Learning for Automated Mitral Regurgitation Detection from Cardiac Imaging. MICCAI (7) 2023: 236-246 - [c92]Huaizu Jiang, Erik G. Learned-Miller:
DCVNet: Dilated Cost Volume Networks for Fast Optical Flow. WACV 2023: 5139-5146 - 2022
- [c91]Tejas Panambur, Deep Chakraborty, Melissa Meyer, Ralph Milliken, Erik G. Learned-Miller, Mario Parente:
Self-Supervised Learning to Guide Scientifically Relevant Categorization of Martian Terrain Images. CVPR Workshops 2022: 1321-1331 - 2021
- [c90]Zitian Chen, Subhransu Maji, Erik G. Learned-Miller:
Shot in the Dark: Few-Shot Learning With No Base-Class Labels. CVPR Workshops 2021: 2668-2677 - [c89]Cheng Gu, Erik G. Learned-Miller, Daniel Sheldon, Guillermo Gallego, Pia Bideau:
The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data. ICCV 2021: 13475-13484 - [c88]My Phan, Philip S. Thomas, Erik G. Learned-Miller:
Towards Practical Mean Bounds for Small Samples. ICML 2021: 8567-8576 - [c87]Yash Chandak, Scott Niekum, Bruno C. da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas:
Universal Off-Policy Evaluation. NeurIPS 2021: 27475-27490 - [c86]Chen Qu, Hamed Zamani, Liu Yang, W. Bruce Croft, Erik G. Learned-Miller:
Passage Retrieval for Outside-Knowledge Visual Question Answering. SIGIR 2021: 1753-1757 - 2020
- [c85]Colin Samplawski, Erik G. Learned-Miller, Heesung Kwon, Benjamin M. Marlin:
Zero-Shot Learning in the Presence of Hierarchically Coarsened Labels. CVPR Workshops 2020: 4015-4019 - [c84]Huaizu Jiang, Ishan Misra, Marcus Rohrbach, Erik G. Learned-Miller, Xinlei Chen:
In Defense of Grid Features for Visual Question Answering. CVPR 2020: 10264-10273 - [c83]Aruni RoyChowdhury, Xiang Yu, Kihyuk Sohn, Erik G. Learned-Miller, Manmohan Chandraker:
Improving Face Recognition by Clustering Unlabeled Faces in the Wild. ECCV (24) 2020: 119-136 - [c82]Matheus Gadelha, Aruni RoyChowdhury, Gopal Sharma, Evangelos Kalogerakis, Liangliang Cao, Erik G. Learned-Miller, Rui Wang, Subhransu Maji:
Label-Efficient Learning on Point Clouds Using Approximate Convex Decompositions. ECCV (10) 2020: 473-491 - [c81]Zhipeng Tang, Fabien Delattre, Pia Bideau, Mark D. Corner, Erik G. Learned-Miller:
C-14: assured timestamps for drone videos. MobiCom 2020: 39:1-39:13 - 2019
- [c80]Ashish Singh, Hang Su, SouYoung Jin, Huaizu Jiang, Chetan Manjesh, Geng Luo, Ziwei He, Li Hong, Erik G. Learned-Miller, Rosie Cowell:
Half&Half: New Tasks and Benchmarks for Studying Visual Common Sense. CVPR Workshops 2019: 1-4 - [c79]Aruni RoyChowdhury, Prithvijit Chakrabarty, Ashish Singh, SouYoung Jin, Huaizu Jiang, Liangliang Cao, Erik G. Learned-Miller:
Automatic adaptation of object detectors to new domains using self-training. CVPR Workshops 2019: 22-32 - [c78]Aruni RoyChowdhury, Prithvijit Chakrabarty, Ashish Singh, SouYoung Jin, Huaizu Jiang, Liangliang Cao, Erik G. Learned-Miller:
Automatic Adaptation of Object Detectors to New Domains Using Self-Training. CVPR 2019: 780-790 - [c77]Hang Su, Varun Jampani, Deqing Sun, Orazio Gallo, Erik G. Learned-Miller, Jan Kautz:
Pixel-Adaptive Convolutional Neural Networks. CVPR 2019: 11166-11175 - [c76]Huaizu Jiang, Deqing Sun, Varun Jampani, Zhaoyang Lv, Erik G. Learned-Miller, Jan Kautz:
SENSE: A Shared Encoder Network for Scene-Flow Estimation. ICCV 2019: 3194-3203 - [c75]Philip S. Thomas, Erik G. Learned-Miller:
Concentration Inequalities for Conditional Value at Risk. ICML 2019: 6225-6233 - 2018
- [c74]Hamed Zamani, Mostafa Dehghani, W. Bruce Croft, Erik G. Learned-Miller, Jaap Kamps:
From Neural Re-Ranking to Neural Ranking: Learning a Sparse Representation for Inverted Indexing. CIKM 2018: 497-506 - [c73]Pia Bideau, Aruni RoyChowdhury, Rakesh R. Menon, Erik G. Learned-Miller:
The Best of Both Worlds: Combining CNNs and Geometric Constraints for Hierarchical Motion Segmentation. CVPR 2018: 508-517 - [c72]Huaizu Jiang, Deqing Sun, Varun Jampani, Ming-Hsuan Yang, Erik G. Learned-Miller, Jan Kautz:
Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation. CVPR 2018: 9000-9008 - [c71]Huaizu Jiang, Gustav Larsson, Michael Maire, Greg Shakhnarovich, Erik G. Learned-Miller:
Self-Supervised Relative Depth Learning for Urban Scene Understanding. ECCV (11) 2018: 20-37 - [c70]SouYoung Jin, Aruni RoyChowdhury, Huaizu Jiang, Ashish Singh, Aditya Prasad, Deep Chakraborty, Erik G. Learned-Miller:
Unsupervised Hard Example Mining from Videos for Improved Object Detection. ECCV (13) 2018: 316-333 - [c69]Pia Bideau, Rakesh R. Menon, Erik G. Learned-Miller:
MoA-Net: Self-supervised Motion Segmentation. ECCV Workshops (6) 2018: 715-730 - [c68]Li Yang Ku, Jonathan Rogers, Philip Strawser, Julia Badger, Erik G. Learned-Miller, Rod Grupen:
A Framework for Dexterous Manipulation. IROS 2018: 4131-4138 - [c67]Li Yang Ku, Scott Michael Jordan, Julia Badger, Erik G. Learned-Miller, Rod Grupen:
Learning to Use a Ratchet by Modeling Spatial Relations in Demonstrations. ISER 2018: 398-410 - [c66]Hamed R. Bonab, Hamed Zamani, Erik G. Learned-Miller, James Allan:
Citation Worthiness of Sentences in Scientific Reports. SIGIR 2018: 1061-1064 - 2017
- [c65]Huaizu Jiang, Erik G. Learned-Miller:
Face Detection with the Faster R-CNN. FG 2017: 650-657 - [c64]Sou-Young Jin, Hang Su, Chris Stauffer, Erik G. Learned-Miller:
End-to-End Face Detection and Cast Grouping in Movies Using Erdös-Rényi Clustering. ICCV 2017: 5286-5295 - [c63]Li Yang Ku, Erik G. Learned-Miller, Roderic A. Grupen:
An aspect representation for object manipulation based on convolutional neural networks. ICRA 2017: 794-800 - [c62]Li Yang Ku, Erik G. Learned-Miller, Roderic A. Grupen:
Associating grasp configurations with hierarchical features in convolutional neural networks. IROS 2017: 2434-2441 - [c61]Haw-Shiuan Chang, Erik G. Learned-Miller, Andrew McCallum:
Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples. NIPS 2017: 1002-1012 - 2016
- [c60]Manolis Savva, Fisher Yu, Hao Su, Masaki Aono, Baoquan Chen, Daniel Cohen-Or, Weihong Deng, Hang Su, Song Bai, Xiang Bai, Noa Fish, Jiajie Han, Evangelos Kalogerakis, Erik G. Learned-Miller, Yangyan Li, Minghui Liao, Subhransu Maji, Atsushi Tatsuma, Yida Wang, Nanhai Zhang, Zhichao Zhou:
Large-Scale 3D Shape Retrieval from ShapeNet Core55. 3DOR@Eurographics 2016 - [c59]Aruni Roy Chowdhury, Daniel Sheldon, Subhransu Maji, Erik G. Learned-Miller:
Distinguishing Weather Phenomena from Bird Migration Patterns in Radar Imagery. CVPR Workshops 2016: 276-283 - [c58]Pia Bideau, Erik G. Learned-Miller:
It's Moving! A Probabilistic Model for Causal Motion Segmentation in Moving Camera Videos. ECCV (8) 2016: 433-449 - [c57]Aruni Roy Chowdhury, Tsung-Yu Lin, Subhransu Maji, Erik G. Learned-Miller:
One-to-many face recognition with bilinear CNNs. WACV 2016: 1-9 - 2015
- [c56]Li Yang Ku, Dirk Ruiken, Erik G. Learned-Miller, Roderic A. Grupen:
Error detection and surprise in stochastic robot actions. Humanoids 2015: 1096-1101 - [c55]Hang Su, Subhransu Maji, Evangelos Kalogerakis, Erik G. Learned-Miller:
Multi-view Convolutional Neural Networks for 3D Shape Recognition. ICCV 2015: 945-953 - [c54]Li Yang Ku, Erik G. Learned-Miller, Roderic A. Grupen:
Modeling Objects as Aspect Transition Graphs to Support Manipulation. ISRR (2) 2015: 127-143 - 2014
- [c53]Andrew Kae, Benjamin M. Marlin, Erik G. Learned-Miller:
The Shape-Time Random Field for Semantic Video Labeling. CVPR 2014: 272-279 - [c52]Laura Sevilla-Lara, Deqing Sun, Erik G. Learned-Miller, Michael J. Black:
Optical Flow Estimation with Channel Constancy. ECCV (1) 2014: 423-438 - [c51]Li Yang Ku, Shiraj Sen, Erik G. Learned-Miller, Roderic A. Grupen:
The Aspect Transition Graph: An Affordance-Based Model. ECCV Workshops (2) 2014: 459-465 - 2013
- [c50]Benjamin Mears, Laura Sevilla-Lara, Erik G. Learned-Miller:
Distribution Fields with Adaptive Kernels for Large Displacement Image Alignment. BMVC 2013 - [c49]Andrew Kae, Kihyuk Sohn, Honglak Lee, Erik G. Learned-Miller:
Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling. CVPR 2013: 2019-2026 - [c48]Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller:
Coherent Motion Segmentation in Moving Camera Videos Using Optical Flow Orientations. ICCV 2013: 1577-1584 - [c47]Yahan Zhou, Jacqueline L. Feild, Erik G. Learned-Miller, Rui Wang:
Scene Text Segmentation via Inverse Rendering. ICDAR 2013: 457-461 - [c46]Jacqueline L. Feild, Erik G. Learned-Miller:
Improving Open-Vocabulary Scene Text Recognition. ICDAR 2013: 604-608 - [c45]Jacqueline L. Feild, Erik G. Learned-Miller, David A. Smith:
Using a Probabilistic Syllable Model to Improve Scene Text Recognition. ICDAR 2013: 897-901 - [c44]Hamed Soroush, Keen Sung, Erik G. Learned-Miller, Brian Neil Levine, Marc Liberatore:
Turning Off GPS Is Not Enough: Cellular Location Leaks over the Internet. Privacy Enhancing Technologies 2013: 103-122 - 2012
- [c43]Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller:
Improvements in Joint Domain-Range Modeling for Background Subtraction. BMVC 2012: 1-11 - [c42]Laura Sevilla-Lara, Erik G. Learned-Miller:
Distribution fields for tracking. CVPR 2012: 1910-1917 - [c41]Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller:
Background modeling using adaptive pixelwise kernel variances in a hybrid feature space. CVPR 2012: 2104-2111 - [c40]Gary B. Huang, Honglak Lee, Erik G. Learned-Miller:
Learning hierarchical representations for face verification with convolutional deep belief networks. CVPR 2012: 2518-2525 - [c39]Gary B. Huang, Marwan A. Mattar, Honglak Lee, Erik G. Learned-Miller:
Learning to Align from Scratch. NIPS 2012: 773-781 - [c38]Marwan A. Mattar, Allen R. Hanson, Erik G. Learned-Miller:
Unsupervised Joint Alignment and Clustering using Bayesian Nonparametrics. UAI 2012: 584-593 - 2011
- [c37]David L. Smith, Jacqueline L. Feild, Erik G. Learned-Miller:
Enforcing similarity constraints with integer programming for better scene text recognition. CVPR 2011: 73-80 - [c36]Vidit Jain, Erik G. Learned-Miller:
Online domain adaptation of a pre-trained cascade of classifiers. CVPR 2011: 577-584 - [c35]Mastooreh Salajegheh, Yue Wang, Kevin Fu, Anxiao Jiang, Erik G. Learned-Miller:
Exploiting Half-Wits: Smarter Storage for Low-Power Devices. FAST 2011: 47-60 - [c34]Robert J. Walls, Erik G. Learned-Miller, Brian Neil Levine:
Forensic Triage for Mobile Phones with DEC0DE. USENIX Security Symposium 2011 - 2010
- [c33]John Tuttle, Robert J. Walls, Erik G. Learned-Miller, Brian Neil Levine:
Reverse engineering for mobile systems forensics with Ares. Insider Threats@CCS 2010: 21-28 - [c32]Gary B. Huang, Erik G. Learned-Miller:
Learning class-specific image transformations with higher-order Boltzmann machines. CVPR Workshops 2010: 25-32 - [c31]Andrew Kae, Gary B. Huang, Carl Doersch, Erik G. Learned-Miller:
Improving state-of-the-art OCR through high-precision document-specific modeling. CVPR 2010: 1935-1942 - 2009
- [c30]Marwan A. Mattar, Michael G. Ross, Erik G. Learned-Miller:
Nonparametric curve alignment. ICASSP 2009: 3457-3460 - [c29]Andrew Kae, Erik G. Learned-Miller:
Learning on the Fly: Font-Free Approaches to Difficult OCR Problems. ICDAR 2009: 571-575 - 2008
- [c28]Gary B. Huang, Manjunath Narayana, Erik G. Learned-Miller:
Towards unconstrained face recognition. CVPR Workshops 2008: 1-8 - [c27]Jerod J. Weinman, Erik G. Learned-Miller, Allen R. Hanson:
A discriminative semi-Markov model for robust scene text recognition. ICPR 2008: 1-5 - 2007
- [c26]Gary B. Huang, Vidit Jain, Erik G. Learned-Miller:
Unsupervised Joint Alignment of Complex Images. ICCV 2007: 1-8 - [c25]Vidit Jain, Erik G. Learned-Miller, Andrew McCallum:
People-LDA: Anchoring Topics to People using Face Recognition. ICCV 2007: 1-8 - [c24]Gary B. Huang, Erik G. Learned-Miller, Andrew McCallum:
Cryptogram Decoding for OCR Using Numerization Strings. ICDAR 2007: 208-212 - [c23]Jerod J. Weinman, Erik G. Learned-Miller, Allen R. Hanson:
Fast Lexicon-Based Scene Text Recognition with Sparse Belief Propagation. ICDAR 2007: 979-983 - [c22]Michael L. Wick, Michael G. Ross, Erik G. Learned-Miller:
Context-Sensitive Error Correction: Using Topic Models to Improve OCR. ICDAR 2007: 1168-1172 - [c21]David Walker Duhon, Jerod J. Weinman, Erik G. Learned-Miller:
Techniques and Applications for Persistent Backgrounding in a Humanoid Torso Robot. ICRA 2007: 3034-3040 - 2006
- [c20]Vidit Jain, Andras Ferencz, Erik G. Learned-Miller:
Discriminative Training of Hyper-feature Models for Object Identification. BMVC 2006: 357-366 - [c19]Jerod J. Weinman, Erik G. Learned-Miller:
Improving Recognition of Novel Input with Similarity. CVPR (1) 2006: 308-315 - [c18]Ron Bekkerman, Mehran Sahami, Erik G. Learned-Miller:
Combinatorial Markov Random Fields. ECML 2006: 30-41 - [c17]Erik G. Learned-Miller, Qifeng Lu, Angela Paisley, Peter Trainer, Volker Blanz, Katrin Dedden, Ralph Miller:
Detecting Acromegaly: Screening for Disease with a Morphable Model. MICCAI (2) 2006: 495-503 - 2005
- [c16]Lilla Zöllei, Erik G. Learned-Miller, W. Eric L. Grimson, William M. Wells III:
Efficient Population Registration of 3D Data. CVBIA 2005: 291-301 - [c15]Marwan A. Mattar, Allen R. Hanson, Erik G. Learned-Miller:
Sign Classification using Local and Meta-Features. CVPR Workshops 2005: 26 - [c14]Dimitri A. Lisin, Marwan A. Mattar, Matthew B. Blaschko, Erik G. Learned-Miller, Mark C. Benfield:
Combining Local and Global Image Features for Object Class Recognition. CVPR Workshops 2005: 47 - [c13]Andras Ferencz, Erik G. Learned-Miller, Jitendra Malik:
Building a Classification Cascade for Visual Identification from One Example. ICCV 2005: 286-293 - [c12]Erik G. Learned-Miller, Vidit Jain:
Many Heads Are Better Than One: Jointly Removing Bias from Multiple MRIs Using Nonparametric Maximum Likelihood. IPMI 2005: 615-626 - 2004
- [c11]Tamara L. Berg, Alexander C. Berg, Jaety Edwards, Michael Maire, Ryan White, Yee Whye Teh, Erik G. Learned-Miller, David A. Forsyth:
Names and Faces in the News. CVPR (2) 2004: 848-854 - [c10]Andras Ferencz, Erik G. Learned-Miller, Jitendra Malik:
Learning Hyper-Features for Visual Identification. NIPS 2004: 425-432 - [c9]Erik G. Learned-Miller, Parvez Ahammad:
Joint MRI Bias Removal Using Entropy Minimization Across Images. NIPS 2004: 761-768 - 2003
- [c8]Erik G. Miller, Christophe Chefd'Hotel:
Practical Non-parametric Density Estimation on a Transformation Group for Vision. CVPR (2) 2003: 114-121 - [c7]Erik G. Miller:
A new class of entropy estimators for multi-dimensional densities. ICASSP (3) 2003: 297-300 - 2002
- [c6]Kinh Tieu, Erik G. Miller:
Unsupervised Color Constancy. NIPS 2002: 1303-1310 - 2001
- [c5]Erik G. Miller, Kinh Tieu:
Color Eigenflows: Statistical Modeling of Joint Color Changes. ICCV 2001: 607-614 - [c4]Simon K. Warfield, Jan Rexilius, Petra S. Huppi, Terrie E. Inder, Erik G. Miller, William M. Wells III, Gary P. Zientara, Ferenc A. Jolesz, Ron Kikinis:
A Binary Entropy Measure to Assess Nonrigid Registration Algorithms. MICCAI 2001: 266-274 - [c3]Chris Stauffer, Erik G. Miller, Kinh Tieu:
Transform-invariant Image Decomposition with Similarity Templates. NIPS 2001: 1295-1302 - 2000
- [c2]Erik G. Miller, Nicholas E. Matsakis, Paul A. Viola:
Learning from One Example through Shared Densities on Transforms. CVPR 2000: 1464-1471 - 1998
- [c1]Erik G. Miller, Paul A. Viola:
Ambiguity and Constraint in Mathematical Expression Recognition. AAAI/IAAI 1998: 784-791
Informal and Other Publications
- 2023
- [i45]Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Dimitri Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha:
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems. CoRR abs/2301.07799 (2023) - [i44]Shifan Zhu, Zhipeng Tang, Michael Yang, Erik G. Learned-Miller, Donghyun Kim:
Event Camera-based Visual Odometry for Dynamic Motion Tracking of a Legged Robot Using Adaptive Time Surface. CoRR abs/2305.08962 (2023) - [i43]Zitian Chen, Mingyu Ding, Yikang Shen, Wei Zhan, Masayoshi Tomizuka, Erik G. Learned-Miller, Chuang Gan:
An Efficient General-Purpose Modular Vision Model via Multi-Task Heterogeneous Training. CoRR abs/2306.17165 (2023) - [i42]Fabien Delattre, David Dirnfeld, Phat Nguyen, Stephen Scarano, Michael J. Jones, Pedro Miraldo, Erik G. Learned-Miller:
Robust Frame-to-Frame Camera Rotation Estimation in Crowded Scenes. CoRR abs/2309.08588 (2023) - [i41]Ke Xiao, Erik G. Learned-Miller, Evangelos Kalogerakis, James Priest, Madalina Fiterau:
Machine Learning for Automated Mitral Regurgitation Detection from Cardiac Imaging. CoRR abs/2310.04871 (2023) - [i40]Bruce Levin, Erik G. Learned-Miller:
Log-Concavity of Multinomial Likelihood Functions Under Interval Censoring Constraints on Frequencies or Their Partial Sums. CoRR abs/2311.02763 (2023) - 2022
- [i39]Pia Bideau, Erik G. Learned-Miller, Cordelia Schmid, Karteek Alahari:
The Right Spin: Learning Object Motion from Rotation-Compensated Flow Fields. CoRR abs/2203.00115 (2022) - [i38]Tejas Panambur, Deep Chakraborty, Melissa Meyer, Ralph Milliken, Erik G. Learned-Miller, Mario Parente:
Self-Supervised Learning to Guide Scientifically Relevant Categorization of Martian Terrain Images. CoRR abs/2204.09854 (2022) - [i37]Ashutosh Singh, Ashish Singh, Aria Masoomi, Tales Imbiriba, Erik G. Learned-Miller, Deniz Erdogmus:
Inv-SENnet: Invariant Self Expression Network for clustering under biased data. CoRR abs/2211.06780 (2022) - [i36]Ashish Singh, Michael J. Jones, Erik G. Learned-Miller:
EVAL: Explainable Video Anomaly Localization. CoRR abs/2212.07900 (2022) - [i35]Zitian Chen, Yikang Shen, Mingyu Ding, Zhenfang Chen, Hengshuang Zhao, Erik G. Learned-Miller, Chuang Gan:
Mod-Squad: Designing Mixture of Experts As Modular Multi-Task Learners. CoRR abs/2212.08066 (2022) - 2021
- [i34]Huaizu Jiang, Erik G. Learned-Miller:
DCVNet: Dilated Cost Volume Networks for Fast Optical Flow. CoRR abs/2103.17271 (2021) - [i33]Yash Chandak, Scott Niekum, Bruno Castro da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas:
Universal Off-Policy Evaluation. CoRR abs/2104.12820 (2021) - [i32]Chen Qu, Hamed Zamani, Liu Yang, W. Bruce Croft, Erik G. Learned-Miller:
Passage Retrieval for Outside-Knowledge Visual Question Answering. CoRR abs/2105.03938 (2021) - [i31]Cheng Gu, Erik G. Learned-Miller, Daniel Sheldon, Guillermo Gallego, Pia Bideau:
The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data. CoRR abs/2106.06887 (2021) - [i30]Gopal Sharma, Bidya Dash, Matheus Gadelha, Aruni RoyChowdhury, Marios Loizou, Evangelos Kalogerakis, Liangliang Cao, Erik G. Learned-Miller, Rui Wang, Subhransu Maji:
SurFit: Learning to Fit Surfaces Improves Few Shot Learning on Point Clouds. CoRR abs/2112.13942 (2021) - 2020
- [i29]Huaizu Jiang, Ishan Misra, Marcus Rohrbach, Erik G. Learned-Miller, Xinlei Chen:
In Defense of Grid Features for Visual Question Answering. CoRR abs/2001.03615 (2020) - [i28]Matheus Gadelha, Aruni RoyChowdhury, Gopal Sharma, Evangelos Kalogerakis, Liangliang Cao, Erik G. Learned-Miller, Rui Wang, Subhransu Maji:
Label-Efficient Learning on Point Clouds using Approximate Convex Decompositions. CoRR abs/2003.13834 (2020) - [i27]Zitian Chen, Zhiqiang Shen, Jiahui Yu, Erik G. Learned-Miller:
Cross-Supervised Object Detection. CoRR abs/2006.15056 (2020) - [i26]Aruni RoyChowdhury, Xiang Yu, Kihyuk Sohn, Erik G. Learned-Miller, Manmohan Chandraker:
Improving Face Recognition by Clustering Unlabeled Faces in the Wild. CoRR abs/2007.06995 (2020) - [i25]Zitian Chen, Subhransu Maji, Erik G. Learned-Miller:
Shot in the Dark: Few-Shot Learning with No Base-Class Labels. CoRR abs/2010.02430 (2020) - [i24]Lijun Zhang, Xiao Liu, Erik G. Learned-Miller, Hui Guan:
SID-NISM: A Self-supervised Low-light Image Enhancement Framework. CoRR abs/2012.08707 (2020) - 2019
- [i23]Marwan A. Mattar, Michael G. Ross, Erik G. Learned-Miller:
Nonparametric Curve Alignment. CoRR abs/1902.00626 (2019) - [i22]Colin Samplawski, Heesung Kwon, Erik G. Learned-Miller, Benjamin M. Marlin:
Integrating Propositional and Relational Label Side Information for Hierarchical Zero-Shot Image Classification. CoRR abs/1902.05492 (2019) - [i21]Hang Su, Varun Jampani, Deqing Sun, Orazio Gallo, Erik G. Learned-Miller, Jan Kautz:
Pixel-Adaptive Convolutional Neural Networks. CoRR abs/1904.05373 (2019) - [i20]Aruni RoyChowdhury, Prithvijit Chakrabarty, Ashish Singh, SouYoung Jin, Huaizu Jiang, Liangliang Cao, Erik G. Learned-Miller:
Automatic adaptation of object detectors to new domains using self-training. CoRR abs/1904.07305 (2019) - [i19]Erik G. Learned-Miller, Philip S. Thomas:
A New Confidence Interval for the Mean of a Bounded Random Variable. CoRR abs/1905.06208 (2019) - [i18]Huaizu Jiang, Deqing Sun, Varun Jampani, Zhaoyang Lv, Erik G. Learned-Miller, Jan Kautz:
SENSE: a Shared Encoder Network for Scene-flow Estimation. CoRR abs/1910.12361 (2019) - 2018
- [i17]SouYoung Jin, Aruni RoyChowdhury, Huaizu Jiang, Ashish Singh, Aditya Prasad, Deep Chakraborty, Erik G. Learned-Miller:
Unsupervised Hard Example Mining from Videos for Improved Object Detection. CoRR abs/1808.04285 (2018) - 2017
- [i16]Haw-Shiuan Chang, Erik G. Learned-Miller, Andrew McCallum:
Active Bias: Training a More Accurate Neural Network by Emphasizing High Variance Samples. CoRR abs/1704.07433 (2017) - [i15]Sou-Young Jin, Hang Su, Chris Stauffer, Erik G. Learned-Miller:
End-to-end Face Detection and Cast Grouping in Movies Using Erdős-Rényi Clustering. CoRR abs/1709.02458 (2017) - [i14]Huaizu Jiang, Deqing Sun, Varun Jampani, Ming-Hsuan Yang, Erik G. Learned-Miller, Jan Kautz:
Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation. CoRR abs/1712.00080 (2017) - [i13]Huaizu Jiang, Erik G. Learned-Miller, Gustav Larsson, Michael Maire, Greg Shakhnarovich:
Self-Supervised Depth Learning for Urban Scene Understanding. CoRR abs/1712.04850 (2017) - 2016
- [i12]Pia Bideau, Erik G. Learned-Miller:
It's Moving! A Probabilistic Model for Causal Motion Segmentation in Moving Camera Videos. CoRR abs/1604.00136 (2016) - [i11]Huaizu Jiang, Erik G. Learned-Miller:
Face Detection with the Faster R-CNN. CoRR abs/1606.03473 (2016) - [i10]Li Yang Ku, Erik G. Learned-Miller, Roderic A. Grupen:
Associating Grasping with Convolutional Neural Network Features. CoRR abs/1609.03947 (2016) - [i9]Pia Bideau, Erik G. Learned-Miller:
A Detailed Rubric for Motion Segmentation. CoRR abs/1610.10033 (2016) - 2015
- [i8]Hang Su, Subhransu Maji, Evangelos Kalogerakis, Erik G. Learned-Miller:
Multi-view Convolutional Neural Networks for 3D Shape Recognition. CoRR abs/1505.00880 (2015) - [i7]Aruni RoyChowdhury, Tsung-Yu Lin, Subhransu Maji, Erik G. Learned-Miller:
Face Identification with Bilinear CNNs. CoRR abs/1506.01342 (2015) - [i6]Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller:
Coherent Motion Segmentation in Moving Camera Videos using Optical Flow Orientations. CoRR abs/1511.01619 (2015) - [i5]Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller:
Background subtraction - separating the modeling and the inference. CoRR abs/1511.01627 (2015) - [i4]Manjunath Narayana, Allen R. Hanson, Erik G. Learned-Miller:
Background Modeling Using Adaptive Pixelwise Kernel Variances in a Hybrid Feature Space. CoRR abs/1511.01631 (2015) - 2012
- [i3]Marwan A. Mattar, Allen R. Hanson, Erik G. Learned-Miller:
Unsupervised Joint Alignment and Clustering using Bayesian Nonparametrics. CoRR abs/1210.4892 (2012) - 2009
- [i2]Andrew Kae, Gary B. Huang, Erik G. Learned-Miller:
Bounding the Probability of Error for High Precision Recognition. CoRR abs/0907.0418 (2009) - 2005
- [i1]Joseph DeStefano, Erik G. Learned-Miller:
A Probabilistic Upper Bound on Differential Entropy. CoRR abs/cs/0504091 (2005)
Coauthor Index
Aruni Roy Chowdhury
aka: Aruni RoyChowdhury
aka: Aruni RoyChowdhury
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