Projects | IU Computer Vision Lab

View projects by: General topic Technical approach Year

Social media mining

Utilizing remote sensing and big data to quantify conflict intensity: The Arab Spring as a case study

Noam Levin, Saleem Ali, David Crandall

Applied Geography 2018

[pdf]

A unified model for near and remote sensing

Scott Workman, Menghua Zhai, David Crandall, Nathan Jacobs

ICCV 2017

[www | pdf]

A deep study into the history of web design

Bardia Doosti, David Crandall, Norman Makoto Su

WEBSCI 2017

[www | pdf]

Tracking Natural Events through Social Media and Computer Vision

Jingya Wang, Mohammed Korayem, Saul Blanco, David Crandall

ACMMM 2016

[www | pdf]

Where have all the people gone? Enhancing global conservation using night lights and social media

Noam Levin, Salit Kark, David Crandall

Ecological Applications 2015

[pdf]

Linking past to present: Discovering style in two centuries of architecture

Stefan Lee, Nicolas Maisonneuve, David Crandall, Alexei Efros, Josef Sivic

ICCP 2015

[www | pdf]

Predicting Geo-informative Attributes in Large-scale Image Collections using Convolutional Neural Networks

Stefan Lee, Haipeng Zhang, David Crandall

WACV 2015

[www | pdf]

Multimodal Learning in Loosely-organized Web Images

Kun Duan, David Crandall, Dhruv Batra

CVPR 2014

[pdf]

SfM with MRFs: Discrete-Continuous Optimization for Large-Scale Structure from Motion

David Crandall, Andrew Owens, Noah Snavely, Daniel Huttenlocher

PAMI 2013

[www | pdf]

Observing the natural world with Flickr

Jingya Wang, Mohammed Korayem, David Crandall

ICCV CVCP Workshop 2013

Best paper award!

[pdf]

Modeling people and places with internet photo collections

David Crandall, Noah Snavely

CACM 2012

[pdf]

Mining Photo-sharing Websites to Study Ecological Phenomena

Haipeng Zhang, Mohammed Korayem, David Crandall, Gretchen LeBuhn

WWW 2012

[www | pdf]

Beyond Co-occurrence: Discovering and Visualizing Tag Relationships from Geo-spatial and Temporal Similarities

Haipeng Zhang, Mohammed Korayem, Erkang You, David Crandall

WSDM 2012

[www | pdf]

Networks of Landmarks, Photos, and People

David Crandall, Noah Snavely

Leonardo 2011

[pdf]

Discrete-Continuous Optimization for Large-scale Structure from Motion

David Crandall, Andrew Owens, Noah Snavely, Daniel Huttenlocher

CVPR 2011

Best paper runner-up!

[www | pdf]

Mapping the World's Photos

David Crandall, Lars Backstrom, Daniel Huttenlocher, Jon Kleinberg

WWW 2009

Best paper honorable mention!

[www | pdf]

Egocentric computer vision

Ego4D: Around the World in 3,000 Hours of Egocentric Video

Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, Miguel Martin, Tushar Nagarajan, Ilija Radosavovic, Santhosh Kumar Ramakrishnan, Fiona Ryan, Jayant Sharma, Michael Wray, Mengmeng Xu, Eric Zhongcong Xu, Chen Zhao, Siddhant Bansal, Dhruv Batra, Vincent Cartillier, Sean Crane, Tien Do, Morrie Doulaty, Akshay Erapalli, Christoph Feichtenhofer, Adriano Fragomeni, Qichen Fu, Christian Fuegen, Abrham Gebreselasie, Cristina Gonzalez, James Hillis, Xuhua Huang, Yifei Huang, Wenqi Jia, Weslie Khoo, Jachym Kolar, Satwik Kottur, Anurag Kumar, Federico Landini, Chao Li, Yanghao Li, Zhenqiang Li, Karttikeya Mangalam, Raghava Modhugu, Jonathan Munro, Tullie Murrell, Takumi Nishiyasu, Will Price, Paola Ruiz Puentes, Merey Ramazanova, Leda Sari, Kiran Somasundaram, Audrey Southerland, Yusuke Sugano, Ruijie Tao, Minh Vo, Yuchen Wang, Xindi Wu, Takuma Yagi, Yunyi Zhu, Pablo Arbelaez, David Crandall, Dima Damen, Giovanni Maria Farinella, Bernard Ghanem, Vamsi Krishna Ithapu, Jawahar, Hanbyul Joo, Kris Kitani, Haizhou Li, Richard Newcombe, Aude Oliva, Hyun Soo Park, James Rehg, Yoichi Sato, Jianbo Shi, Mike Zheng Shou, Antonio Torralba, Lorenzo Torresani, Mingfei Yan, Jitendra Malik

CVPR 2022

[pdf]

Whose hand is this? Person Identification from Egocentric Hand Gestures

Satoshi Tsutsui, Yanwei Fu, David Crandall

WACV 2021

[pdf]

Localizing novel attended objects in egocentric views

Shujon Naha, Md Alimoor Reza, Chen Yu, David Crandall

BMVC 2020

[pdf]

HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation

Bardia Doosti, Shujon Naha, Majid Mirbagheri, David Crandall

CVPR 2020

[www | pdf]

Interaction Graph for Object Importance Estimation in On-road Driving Videos

Zehua Zhang, Ashish Tawari, Sujitha Martin, David Crandall

ICRA 2020

[pdf]

Unsupervised Traffic Accident Detection in First-Person Videos

Yu Yao, Mingze Xu, Yuchen Wang, David Crandall, Ella Atkins

IROS 2019

[pdf]

A Self Validation Network for Object-Level Human Attention Estimation

Zehua Zhang, Chen Yu, David Crandall

NeurIPS 2019

[www | pdf]

Embodied Visual Recognition: Learning to Move for Amodal Perception

Jianwei Yang, Zhile Ren, Mingze Xu, Xinlei Chen, David Crandall, Devi Parikh, Dhruv Batria

ICCV 2019

[pdf]

Temporal Recurrent Networks for Online Action Detection

Mingze Xu, Mingfei Gao, Yi-Ting Chen, Larry Davis, David Crandall

ICCV 2019

[pdf]

Egocentric Vision-based Future Vehicle Localization for Intelligent Driving Assistance Systems

Yu Yao, Mingze Xu, Chiho Choi, David Crandall, Ella Atkins, Behzad Dariush

ICRA 2019

[pdf]

From Coarse Attention to Fine-Grained Gaze: A Two-stage 3D Fully Convolutional Network for Predicting Eye Gaze in First Person Video

Zehua Zhang, Sven Bambach, David Crandall, Chen Yu

BMVC 2018

[www | pdf]

Deepdiary: Lifelogging image captioning and summarization

Chenyou Fan, Zehua Zhang, David Crandall

JVCI 2018

[www ]

Object recognition

Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning

Zehua Zhang, David Crandall

WACV 2022

[pdf]

Learning Video Object Segmentation from Unlabeled Videos

Xiankai Lu, Wenguan Wang, Jianbing Shen, Yu-Wing Tai, David Crandall, Steven Hoi

CVPR 2020

[pdf]

Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition

Satoshi Tsutsui, Yanwei Fu, David Crandall

NeurIPS 2019

[www | pdf]

Toddler-Inspired Visual Object Learning

Sven Bambach, David Crandall, Linda Smith, Chen Yu

NeurIPS 2018

[pdf]

A Data Driven Approach for Compound Figure Separation Using Convolutional Neural Networks

Satoshi Tsutsui, David Crandall

ICDAR 2017

[www | pdf]

Recognizing landmarks in large-scale social image collections

David Crandall, Yunpeng Li, Stefan Lee, Daniel Huttenlocher

Visual Analysis and Geolocalization of Large Scale Imagery 2016

[pdf]

Privacy and security

Semantically Stealthy Adversarial Attacks against Segmentation Models

Zhenhua Chen, Chuhua Wang, David Crandall

WACV 2022

[pdf]

Deep Neural Network-based Detection and Verification of Microelectronic Images

Md Alimoor Reza, Zhenhua Chen, David Crandall

Journal of Hardware and Systems Security 2020

[pdf]

Automatically Detecting Bystanders in Photos to Reduce Privacy Risks

Rakibul Hasan, David Crandall, Mario Fritz, Apu Kapadia

OAKLAND 2020

[pdf]

Fully-Coupled Two-Stream Spatiotemporal Networks for Extremely Low Resolution Action Recognition

Mingze Xu, Aidean Sharghi, Xin Chen, David Crandall

WACV 2018

[pdf]

Addressing supply chain risks of microelectronic devices through computer vision

Zhenhua Chen, Tingyi Wanyan, Ramya Rao, Benjamin Cutilli, James Sowinski, David Crandall, Robert Templeman

AIPR 2017

[pdf]

Cartooning for enhanced privacy in lifelogging and streaming video

Eman Hassan, Rakibul Hasan, Patrick Shaffer, David Crandall, Apu Kapadia

CVPR CV-COPS 2017 2017

[pdf]

Enhancing Lifelogging Privacy by Detecting Screens

Mohammed Korayem, Robert Templeman, Dennis Chen, David Crandall, Apu Kapadia

CHI 2016

Honorable Mention Award!

[www | pdf]

PlaceAvoider: Steering First-Person Cameras away from Sensitive Spaces

Robert Templeman, Mohammed Korayem, David Crandall, Apu Kapadia

NDSS 2014

[pdf]

Reactive Security: Responding to Visual Stimuli from Wearable Cameras

Robert Templeman, Roberto Hoyle, David Crandall, Apu Kapadia

Ubicomp UPSIDE Workshop 2014

[pdf]

PlaceRaider: Virtual Theft in Physical Spaces with Smartphones

Robert Templeman, Zahidur Rahman, David Crandall, Apu Kapadia

NDSS 2013

[www | pdf]

Human visual learning

Learning the generative principles of a symbol system from limited examples

Lei Yuan, Violet Xiang, David Crandall, Linda Smith

Cognition 2020

[pdf]

A Computational Model of Early Word Learning from the Infant's Point of View

Satoshi Tsutsui, Arjun Chandrasekaran, Md Alimoor Reza, David Crandall, Chen Yu

COGSCI 2020

[pdf]

How do infants start learning object names in a sea of clutter?

Hadar Karmazyn Raz, Drew Abney, David Crandall, Chen Yu, Linda Smith

COGSCI 2019

[pdf]

An Egocentric Perspective on Active Vision and Visual Object Learning in Toddlers

Sven Bambach, David Crandall, Linda Smith, Chen Yu

ICDL 2017

[pdf]

Exploring inter-observer differences in first-person object views using deep learning models

Sven Bambach, Zehua Zhang, David Crandall, Chen Yu

ICCV MBCC 2017 2017

[pdf]

Objects in the Center: How the Infant's Body Constrains Infant Scenes

Sven Bambach, Linda Smith, David Crandall, Chen Yu

ICDL 2016

Best paper award!

[pdf]

Active Viewing in Toddlers Facilitates Visual Object Learning: An Egocentric Vision Approach

Sven Bambach, David Crandall, Linda Smith, Chen Yu

COGSCI 2016

[pdf]

Detecting Hands in Children's Egocentric Views to Understand Embodied Attention during Social Interaction

Sven Bambach, John Franchak, David Crandall, Chen Yu

COGSCI 2014

[pdf]

Understanding Embodied Visual Attention in Child-Parent Interaction

Sven Bambach, David Crandall, Chen Yu

ICDL 2013

[pdf]

Wearable camera attitudes and opportunities

Privacy Norms and Preferences for Photos Posted Online

Roberto Hoyle, Luke Stark, Qatrunnada Ismail, David Crandall, Apu Kapadia, Denise Anthony

TOCHI 2020

[pdf]

Can Privacy Be Satisfying? On Improving Viewer Satisfaction for Privacy-Enhanced Photos Using Aesthetic Transforms

Rakibul Hasan, Yifang Li, Eman Hassan, Kelly Caine, David Crandall, Roberto Hoyle, Apu Kapadia

CHI 2019

[pdf]

Viewer Experience of Obscuring Scene Elements in Photos to Enhance Privacy

Rakibul Hasan, Eman Hassan, Yifang Li, Kelly Caine, David Crandall, Roberto Hoyle, Apu Kapadia

CHI 2018

[pdf]

Addressing Physical Safety, Security, and Privacy for People with Visual Impairments

Tousif Ahmed, Patrick Shaffer, Kay Connelly, David Crandall, Apu Kapadia

SOUPS 2016

[pdf]

Sensitive Lifelogs: A Privacy Analysis of Photos from Wearable Cameras

Roberto Hoyle, Robert Templeman, Denise Anthony, David Crandall, Apu Kapadia

CHI 2015

[pdf]

Privacy Concerns and Behaviors of People with Visual Impairments

Tousif Ahmed, Roberto Hoyle, Kay Connelly, David Crandall, Apu Kapadia

CHI 2015

[pdf]

Privacy Behaviors of Lifeloggers using Wearable Cameras

Roberto Hoyle, Robert Templeman, Steven Armes, Denise Anthony, David Crandall, Apu Kapadia

UBICOMP 2014

[pdf]

Machine learning

Generating Counterfactual Images: Toward a C2C-VAE Approach

Ziwei Zhao, David Leake, Xiaomeng Ye, David Crandall

ICCBR Workshop on CBR for Explanation of Intelligent Systems 2022

[pdf]

Controlling the Quality of Distillation in Response-Based Network Compression

Vibhas Vats, David Crandall

AAAI International Workshop on Practical Deep Learning in the Wild 2022

[pdf]

Learning Adaptations for Case-Based Classification: A Neural Network Approach

Xiaomeng Ye, David Leake, Vahid Jalali, David Crandall

ICCBR 2021

[pdf]

On Combining Knowledge-Engineered and Network-Extracted Features for Retrieval

Zachary Wilkerson, David Leake, David Crandall

ICCBR 2021

[pdf]

Diverse Beam Search for Improved Description of Complex Scenes

Ashwin Vijayakumar, Michael Cogswell, Ramprasaath Selvaraju, Qing Sun, Stefan Lee, David Crandall, Dhruv Batra

AAAI 2018

[pdf]

Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles

Stefan Lee, Senthil Purushwalkam, Michael Cogswell, Viresh Ranjan, David Crandall, Dhruv Batra

NeurIPS 2016

[pdf]

Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models

Ashwin K Vijayakumar, Michael Cogswell, Ramprasath Selvaraju, Qing Sun, Stefan Lee, David Crandall, Dhruv Batra

2016

[pdf]

Computer vision for glaciology[More details on these projects]

Deep Tiered Image Segmentation for Detecting Internal Ice Layers in Radar Imagery

Yuchen Wang, Mingze Xu, John Paden, Lara Koenig, Geoffrey Fox, David Crandall

ICME 2021

[pdf]

Automated Ice-Bottom Tracking of 2D and 3D Ice Radar Imagery Using Viterbi and TRW-S

Victor Berger, Mingze Xu, Mohanad Al-Ibadi, Shane Chu, David Crandall, John Paden, Geoffrey Fox

JSTARS 2019

[pdf]

Multi-Task Spatiotemporal Neural Networks for Structured Surface Reconstruction

Mingze Xu, Chenyou Fan, John Paden, Geoffrey Fox, David Crandall

WACV 2018

[pdf]

Automatic estimation of ice bottom surfaces from radar imagery

Mingze Xu, David Crandall, Geoffrey Fox, John Paden

ICIP 2017

[pdf]

Estimating Bedrock and Surface Layer Boundaries and Confidence Intervals in Ice Sheet Radar Imagery using MCMC

Stefan Lee, Jerome Mitchell, David Crandall, Geoffrey Fox

ICIP 2014

[www | pdf]

Automatic Near Surface Estimation from Snow Radar Imagery

Jerome Mitchell, David Crandall, Geoffrey Fox, John Paden

IGARSS 2013

[pdf]

Layer-finding in radar echograms using probabilistic graphical models

David Crandall, Geoffrey Fox, John Paden

ICPR 2012

[www | pdf]

Modeling social networks

De-anonymizing users across heterogeneous social computing platforms

Mohammed Korayem, David Crandall

ICWSM 2013

[pdf]

Chelsea Won, and You Bought a T-shirt: Characterizing the Interplay Between Twitter and E-Commerce

Haipeng Zhang, Nish Parikh, Gyanit Singh, Neel Sundaresan

ASONAM 2013

Best paper award!

[pdf]

Inferring Social Ties from Geographic Coincidences

David Crandall, Lars Backstrom, Daniel Cosley, Siddharth Suri, Daniel Huttenlocher, Jon Kleinberg

PNAS 2010

[pdf]

Feedback Effects between Similarity and Social Influence in Online Communities

David Crandall, Daniel Cosley, Daniel Huttenlocher, Jon Kleinberg, Sid Suri

KDD 2008

[pdf]

Other projects

The Affective Growth of Computer Vision

Norman Su, David Crandall

CVPR 2021

[pdf]

Investigating the Homogenization of Web Design: A Mixed-Methods Approach

Sam Goree, Bardia Doosti, David Crandall, Norman Su

CHI 2021

[pdf]

Automatic Annotation for Semantic Segmentation in Indoor Scenes

Md Alimoor Reza, Akshay Naik, Kai Chen, David Crandall

IROS 2019

[pdf]

Empowering Borrowers in their Choice of Lenders: Decoding Service Quality from Customer Complaints

Aniruddha Godbole, David Crandall

WEBSCI 2019

[pdf]

Observing Pianist Accuracy and Form with Computer Vision

Jangwon Lee, Bardia Doosti, Yupeng Gu, David Cartledge, David Crandall, Christopher Raphael

WACV 2019

[pdf]

Hello Research! Developing an Intensive Research Experience for Undergraduate Women

Suzanne Menzel, Katie Siek, David Crandall

SIGCSE 2019

[www | pdf]

Towards Detecting Dyslexia in Children's Handwriting Using Neural Networks

Katie Spoon, David Crandall, Katie Siek

ICML Workshop on AI for Social Good 2019

[www | pdf]

Minimizing Supervision for Free-space Segmentation

Satoshi Tsutsui, Tommi Kerola, Shunta Saito, David Crandall

CVPR Workshop on Autonomous Driving 2018

[pdf]

Understanding the Aesthetic Evolution of Websites: Towards a Notion of Design Periods

Wen Chen, David Crandall, Norman Su

CHI 2017

[pdf]

From funding agencies to scientific agency: Collective allocation of science funding as an alternative to peer review

Johan Bollen, David Crandall, Damion Junk, Ying Ding, Katy Borner

EMBO Reports 2014

[pdf]

mFingerprint: Privacy-preserving user modeling with multimodal mobile device footprints

Haipeng Zhang, Zhixian Yan, Jun Yang, Emmanuel Munguia Tapia, David Crandall

SBP 2014

[pdf]

Solving Avatar Captchas automatically

Mohammed Korayem, Abdallah Mohamed, David Crandall, Roman Yampolskiy

AMLTA 2012

[pdf]