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David J. Crandall
David Crandall 0001
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- affiliation: Indiana University, Bloomington, USA
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2020 – today
- 2024
- [j31]Samuel Goree, Gabriel Appleby, David Crandall, Norman Makoto Su:
Attention is All They Need: Exploring the Media Archaeology of the Computer Vision Research Paper. Proc. ACM Hum. Comput. Interact. 8(CSCW2): 1-25 (2024) - [j30]Satoshi Tsutsui, Yanwei Fu, David J. Crandall:
Reinforcing Generated Images via Meta-Learning for One-Shot Fine-Grained Visual Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 46(3): 1455-1463 (2024) - [j29]Wencheng Han, Xingping Dong, Yiyuan Zhang, David J. Crandall, Cheng-Zhong Xu, Jianbing Shen:
Asymmetric Convolution: An Efficient and Generalized Method to Fuse Feature Maps in Multiple Vision Tasks. IEEE Trans. Pattern Anal. Mach. Intell. 46(11): 7363-7376 (2024) - [c135]Long-Jing Hsu, Philip B. Stafford, Weslie Khoo, Manasi Swaminathan, Kyrie Jig Amon, Hiroki Sato, Katherine M. Tsui, David J. Crandall, Selma Sabanovic:
"Give it Time: " Longitudinal Panels Scaffold Older Adults' Learning and Robot Co-Design. HRI 2024: 283-292 - [c134]Long-Jing Hsu, Weslie Khoo, Peter Lenon Goshomi, Philip B. Stafford, Manasi Swaminathan, Katherine M. Tsui, David J. Crandall, Selma Sabanovic:
Is Now a Good Time? Opportune Moments for Interacting with an Ikigai Support Robot. HRI (Companion) 2024: 549-553 - [c133]Manasi Swaminathan, Long-Jing Hsu, Min Min Thant, Kyrie Jig Amon, Anna S. Kim, Katherine M. Tsui, Selma Sabanovic, David J. Crandall, Weslie Khoo:
If [YourName] Can Code, So Can You! End-User Robot Programming For Non-Experts. HRI (Companion) 2024: 1033-1037 - [c132]Zachary Wilkerson, David Leake, Vibhas Vats, David Crandall:
Extracting Indexing Features for CBR from Deep Neural Networks: A Transfer Learning Approach. ICCBR 2024: 143-158 - [c131]Xiaomeng Ye, David Leake, Yu Wang, Ziwei Zhao, David Crandall:
Towards Network Implementation of CBR: Case Study of a Neural Network K-NN Algorithm. ICCBR 2024: 354-370 - [c130]Long-Jing Hsu, Weslie Khoo, Manasi Swaminathan, Kyrie Jig Amon, Rasika Muralidharan, Hiroki Sato, Min Min Thant, Anna S. Kim, Katherine M. Tsui, David J. Crandall, Selma Sabanovic:
Let's Talk About You: Development and Evaluation of an Autonomous Robot to Support Ikigai Reflection in Older Adults. RO-MAN 2024: 1323-1330 - [c129]Vibhas K. Vats, Sripad Joshi, David J. Crandall, Md. Alimoor Reza, Soon-Heung Jung:
GC-MVSNet: Multi-View, Multi-Scale, Geometrically-Consistent Multi-View Stereo. WACV 2024: 3230-3240 - [i61]Mang Ye, Shuoyi Chen, Chenyue Li, Wei-Shi Zheng, David Crandall, Bo Du:
Transformer for Object Re-Identification: A Survey. CoRR abs/2401.06960 (2024) - [i60]Vibhas K. Vats, David J. Crandall:
Geometric Constraints in Deep Learning Frameworks: A Survey. CoRR abs/2403.12431 (2024) - [i59]Ziwei Zhao, David Leake, Xiaomeng Ye, David J. Crandall:
Case-Enhanced Vision Transformer: Improving Explanations of Image Similarity with a ViT-based Similarity Metric. CoRR abs/2407.16981 (2024) - 2023
- [j28]Long-Jing Hsu, Waki Kamino, Weslie Khoo, Katherine M. Tsui, David J. Crandall, Selma Sabanovic:
Working Together Toward ikigai: Co-Designing Robots That Can Help Us Achieve Meaning and Purpose in Life. XRDS 30(1): 38-45 (2023) - [j27]Filippo Menczer, David J. Crandall, Yong-Yeol Ahn, Apu Kapadia:
Addressing the harms of AI-generated inauthentic content. Nat. Mac. Intell. 5(7): 679-680 (2023) - [j26]Yu Yao, Xizi Wang, Mingze Xu, Zelin Pu, Yuchen Wang, Ella M. Atkins, David J. Crandall:
DoTA: Unsupervised Detection of Traffic Anomaly in Driving Videos. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 444-459 (2023) - [j25]Antonino Furnari, David J. Crandall, Dima Damen, Kristen Grauman, Giovanni Maria Farinella:
Editorial: Special Section on Egocentric Perception. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 6602-6604 (2023) - [j24]Tianfei Zhou, Fatih Porikli, David J. Crandall, Luc Van Gool, Wenguan Wang:
A Survey on Deep Learning Technique for Video Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 7099-7122 (2023) - [j23]Junbo Yin, Jianbing Shen, Xin Gao, David J. Crandall, Ruigang Yang:
Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection From Point Clouds. IEEE Trans. Pattern Anal. Mach. Intell. 45(8): 9822-9835 (2023) - [j22]Zheng Chen, Zhengming Ding, David J. Crandall, Lantao Liu:
Polyline Generative Navigable Space Segmentation for Autonomous Visual Navigation. IEEE Robotics Autom. Lett. 8(4): 2054-2061 (2023) - [j21]Samuel Goree, David Crandall, Norman Makoto Su:
"It Was Really All About Books:" Speech-like Techno-Masculinity in the Rhetoric of Dot-Com Era Web Design Books. ACM Trans. Comput. Hum. Interact. 30(2): 1-27 (2023) - [c128]Samuel Goree, Weslie Khoo, David J. Crandall:
Correct for Whom? Subjectivity and the Evaluation of Personalized Image Aesthetics Assessment Models. AAAI 2023: 11818-11827 - [c127]Jane Yang, Linda Smith, David Crandall, Chen Yu:
Using manual actions to create visual saliency: an outside-in solution to sustained attention and joint attention. CogSci 2023 - [c126]Feng Cheng, Xizi Wang, Jie Lei, David J. Crandall, Mohit Bansal, Gedas Bertasius:
VindLU: A Recipe for Effective Video-and-Language Pretraining. CVPR 2023: 10739-10750 - [c125]Weslie Khoo, Long-Jing Hsu, Kyrie Jig Amon, Pranav Vijay Chakilam, Wei-Chu Chen, Zachary Kaufman, Agness Lungu, Hiroki Sato, Erin Seliger, Manasi Swaminathan, Katherine M. Tsui, David J. Crandall, Selma Sabanovic:
Spill the Tea: When Robot Conversation Agents Support Well-being for Older Adults. HRI (Companion) 2023: 178-182 - [c124]David Leake, Zachary Wilkerson, Vibhas Vats, Karan Acharya, David J. Crandall:
Examining the Impact of Network Architecture on Extracted Feature Quality for CBR. ICCBR 2023: 3-18 - [c123]Imran Kabir, Shubham Shaurya, Vijayalaxmi Maigur, Nikhil Thakurdesai, Mahesh Latnekar, Mayank Raunak, David J. Crandall, Md. Alimoor Reza:
Few-Shot Segmentation and Semantic Segmentation for Underwater Imagery. IROS 2023: 11451-11457 - [c122]Long-Jing Hsu, Weslie Khoo, Natasha Randall, Waki Kamino, Swapna Joshi, Hiroki Sato, David J. Crandall, Katherine M. Tsui, Selma Sabanovic:
Finding its Voice: The Influence of Robot Voice on Fit, Social Attributes, and Willingness to Use Among Older Adults in the U.S. and Japan. RO-MAN 2023: 2072-2079 - [p2]David Leake, Zachary Wilkerson, Xiaomeng Ye, David J. Crandall:
Enhancing Case-Based Reasoning with Neural Networks. Compendium of Neurosymbolic Artificial Intelligence 2023: 387-409 - [i58]Xizi Wang, Feng Cheng, Gedas Bertasius, David Crandall:
LoCoNet: Long-Short Context Network for Active Speaker Detection. CoRR abs/2301.08237 (2023) - [i57]Zheng Chen, Deepak Duggirala, David Crandall, Lei Jiang, Lantao Liu:
SePaint: Semantic Map Inpainting via Multinomial Diffusion. CoRR abs/2303.02737 (2023) - [i56]Zhenhua Chen, David Crandall:
A Tensor-based Convolutional Neural Network for Small Dataset Classification. CoRR abs/2303.17061 (2023) - [i55]Samuel Goree, David Crandall:
Situated Cameras, Situated Knowledges: Towards an Egocentric Epistemology for Computer Vision. CoRR abs/2307.00064 (2023) - [i54]Vibhas K. Vats, Sripad Joshi, David J. Crandall, Md. Alimoor Reza, Soon-Heung Jung:
GC-MVSNet: Multi-View, Multi-Scale, Geometrically-Consistent Multi-View Stereo. CoRR abs/2310.19583 (2023) - 2022
- [j20]Xiankai Lu, Wenguan Wang, Jianbing Shen, David Crandall, Jiebo Luo:
Zero-Shot Video Object Segmentation With Co-Attention Siamese Networks. IEEE Trans. Pattern Anal. Mach. Intell. 44(4): 2228-2242 (2022) - [j19]Xiankai Lu, Wenguan Wang, Jianbing Shen, David J. Crandall, Luc Van Gool:
Segmenting Objects From Relational Visual Data. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 7885-7897 (2022) - [j18]Chuhua Wang, Yuchen Wang, Mingze Xu, David J. Crandall:
Stepwise Goal-Driven Networks for Trajectory Prediction. IEEE Robotics Autom. Lett. 7(2): 2716-2723 (2022) - [c121]Yayun Zhang, Ellis Cain, David Crandall, Chen Yu:
Grounding Action Verbs in Egocentric Visual Perception. CogSci 2022 - [c120]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, Abrham Gebreselasie, Cristina González, James Hillis, Xuhua Huang, Yifei Huang, Wenqi Jia, Weslie Khoo, Jáchym Kolár, 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, Ziwei Zhao, Yunyi Zhu, Pablo Arbeláez, David Crandall, Dima Damen, Giovanni Maria Farinella, Christian Fuegen, Bernard Ghanem, Vamsi Krishna Ithapu, C. V. Jawahar, Hanbyul Joo, Kris Kitani, Haizhou Li, Richard A. Newcombe, Aude Oliva, Hyun Soo Park, James M. Rehg, Yoichi Sato, Jianbo Shi, Mike Zheng Shou, Antonio Torralba, Lorenzo Torresani, Mingfei Yan, Jitendra Malik:
Ego4D: Around the World in 3, 000 Hours of Egocentric Video. CVPR 2022: 18973-18990 - [c119]Zehua Zhang, David Crandall, Michael J. Proulx, Sachin S. Talathi, Abhishek Sharma:
Can Gaze Inform Egocentric Action Recognition? ETRA 2022: 33:1-33:7 - [c118]David Leake, Zachary Wilkerson, David Crandall:
Extracting Case Indices from Convolutional Neural Networks: A Comparative Study. ICCBR 2022: 81-95 - [c117]Xiaomeng Ye, David Leake, David Crandall:
Case Adaptation with Neural Networks: Capabilities and Limitations. ICCBR 2022: 143-158 - [c116]Ziwei Zhao, David Leake, Xiaomeng Ye, David J. Crandall:
Generating Counterfactual Images: Towards a C2C-VAE Approach. ICCBR Workshops 2022: 189-194 - [c115]Zachary Wilkerson, David Leake, David Crandall:
Leveraging SHAP and CBR for Dimensionaltiy Reduction on the Psychology Prediction Dataset. ICCBR Workshops 2022: 236-240 - [c114]Xiaomeng Ye, Ziwei Zhao, David Leake, David Crandall:
Generation and Evaluation of Creative Images from Limited Data: A Class-to-Class VAE Approach. ICCC 2022: 314-323 - [c113]Satoshi Tsutsui, Xizi Wang, Guangyuan Weng, Yayun Zhang, David J. Crandall, Chen Yu:
Action Recognition based on Cross-Situational Action-object Statistics. ICDL 2022: 355-361 - [c112]Zehua Zhang, David Crandall:
Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning. WACV 2022: 975-985 - [c111]Zhenhua Chen, Chuhua Wang, David Crandall:
Semantically Stealthy Adversarial Attacks against Segmentation Models. WACV 2022: 2846-2855 - [i53]Satoshi Tsutsui, Yanwei Fu, David Crandall:
Reinforcing Generated Images via Meta-learning for One-Shot Fine-Grained Visual Recognition. CoRR abs/2204.10689 (2022) - [i52]Junbo Yin, Jianbing Shen, Xin Gao, David Crandall, Ruigang Yang:
Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection from Point Clouds. CoRR abs/2207.12659 (2022) - [i51]Satoshi Tsutsui, Xizi Wang, Guangyuan Weng, Yayun Zhang, David J. Crandall, Chen Yu:
Action Recognition based on Cross-Situational Action-object Statistics. CoRR abs/2208.07344 (2022) - [i50]Samuel Goree, Gabriel Appleby, David J. Crandall, Norman Makoto Su:
Attention is All They Need: Exploring the Media Archaeology of the Computer Vision Research Paper. CoRR abs/2209.11200 (2022) - [i49]Feng Cheng, Xizi Wang, Jie Lei, David J. Crandall, Mohit Bansal, Gedas Bertasius:
VindLU: A Recipe for Effective Video-and-Language Pretraining. CoRR abs/2212.05051 (2022) - 2021
- [c110]David Leake, Xiaomeng Ye, David J. Crandall:
Supporting Case-Based Reasoning with Neural Networks: An Illustration for Case Adaptation. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering 2021 - [c109]Samuel Goree, Bardia Doosti, David J. Crandall, Norman Makoto Su:
Investigating the Homogenization of Web Design: A Mixed-Methods Approach. CHI 2021: 575:1-575:14 - [c108]Andrei Amatuni, Sara E. Schroer, Yayun Zhang, Ryan E. Peters, Md. Alimoor Reza, David Crandall, Chen Yu:
In-the-Moment Visual Information from the Infant's Egocentric View Determines the Success of Infant Word Learning: A Computational Study. CogSci 2021 - [c107]Ryan E. Peters, Andrei Amatuni, Sara E. Schroer, Shujon Naha, David Crandall, Chen Yu:
Modeling joint attention from egocentric vision. CogSci 2021 - [c106]Yayun Zhang, Andrei Amatuni, Ellis Cain, Xizi Wang, David Crandall, Chen Yu:
Human Learners Integrate Visual and Linguistic Information Cross-Situational Verb Learning. CogSci 2021 - [c105]Norman Makoto Su, David J. Crandall:
The Affective Growth of Computer Vision. CVPR 2021: 9291-9300 - [c104]Zachary Wilkerson, David Leake, David J. Crandall:
On Combining Knowledge-Engineered and Network-Extracted Features for Retrieval. ICCBR 2021: 248-262 - [c103]Xiaomeng Ye, David Leake, Vahid Jalali, David J. Crandall:
Learning Adaptations for Case-Based Classification: A Neural Network Approach. ICCBR 2021: 279-293 - [c102]Yuchen Wang, Mingze Xu, John D. Paden, Lora S. Koenig, Geoffrey C. Fox, David J. Crandall:
Deep Tiered Image Segmentation for Detecting Internal ICE Layers in Radar Imagery. ICME 2021: 1-6 - [c101]Jagpreet Chawla, Nikhil Thakurdesai, Anuj Godase, Md. Alimoor Reza, David J. Crandall, Soon-Heung Jung:
Error Diagnosis of Deep Monocular Depth Estimation Models. IROS 2021: 5344-5649 - [c100]Shujon Naha, Qingyang Xiao, Prianka Banik, Md. Alimoor Reza, David J. Crandall:
Part Segmentation of Unseen Objects using Keypoint Guidance. WACV 2021: 1741-1749 - [c99]Satoshi Tsutsui, Yanwei Fu, David J. Crandall:
Whose hand is this? Person Identification from Egocentric Hand Gestures. WACV 2021: 3398-3407 - [i48]Chuhua Wang, Yuchen Wang, Mingze Xu, David J. Crandall:
Stepwise Goal-Driven Networks for Trajectory Prediction. CoRR abs/2103.14107 (2021) - [i47]Zhenhua Chen, Chuhua Wang, David J. Crandall:
Adversarial Attack in the Context of Self-driving. CoRR abs/2104.01732 (2021) - [i46]Zhenhua Chen, Xiwen Li, Qian Lou, David J. Crandall:
How to Accelerate Capsule Convolutions in Capsule Networks. CoRR abs/2104.02621 (2021) - [i45]Satoshi Tsutsui, David J. Crandall, Chen Yu:
Reverse-engineer the Distributional Structure of Infant Egocentric Views for Training Generalizable Image Classifiers. CoRR abs/2106.06694 (2021) - [i44]Wenguan Wang, Tianfei Zhou, Fatih Porikli, David Crandall, Luc Van Gool:
A Survey on Deep Learning Technique for Video Segmentation. CoRR abs/2107.01153 (2021) - [i43]Xiaomeng Ye, Ziwei Zhao, David Leake, Xizi Wang, David J. Crandall:
Applying the Case Difference Heuristic to Learn Adaptations from Deep Network Features. CoRR abs/2107.07095 (2021) - [i42]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 González, James Hillis, Xuhua Huang, Yifei Huang, Wenqi Jia, Weslie Khoo, Jáchym Kolár, 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 Arbeláez, David Crandall, Dima Damen, Giovanni Maria Farinella, Bernard Ghanem, Vamsi Krishna Ithapu, C. V. Jawahar, Hanbyul Joo, Kris Kitani, Haizhou Li, Richard A. Newcombe, Aude Oliva, Hyun Soo Park, James M. Rehg, Yoichi Sato, Jianbo Shi, Mike Zheng Shou, Antonio Torralba, Lorenzo Torresani, Mingfei Yan, Jitendra Malik:
Ego4D: Around the World in 3, 000 Hours of Egocentric Video. CoRR abs/2110.07058 (2021) - [i41]Zheng Chen, Zhengming Ding, David Crandall, Lantao Liu:
Polyline Based Generative Navigable Space Segmentation for Autonomous Visual Navigation. CoRR abs/2111.00063 (2021) - [i40]Jagpreet Chawla, Nikhil Thakurdesai, Anuj Godase, Md. Alimoor Reza, David J. Crandall, Soon-Heung Jung:
Error Diagnosis of Deep Monocular Depth Estimation Models. CoRR abs/2112.05533 (2021) - [i39]Vibhas Vats, David Crandall:
Controlling the Quality of Distillation in Response-Based Network Compression. CoRR abs/2112.10047 (2021) - 2020
- [j17]Md. Alimoor Reza, Kai Chen, Akshay U. Naik, David J. Crandall, Soon-Heung Jung:
Automatic Dense Annotation for Monocular 3D Scene Understanding. IEEE Access 8: 68852-68865 (2020) - [j16]Md. Alimoor Reza, Zhenhua Chen, David J. Crandall:
Deep Neural Network-Based Detection and Verification of Microelectronic Images. J. Hardw. Syst. Secur. 4(1): 44-54 (2020) - [j15]Roberto Hoyle, Luke Stark, Qatrunnada Ismail, David J. Crandall, Apu Kapadia, Denise L. Anthony:
Privacy Norms and Preferences for Photos Posted Online. ACM Trans. Comput. Hum. Interact. 27(4): 30:1-30:27 (2020) - [c98]Md. Alimoor Reza, David J. Crandall:
IC-ChipNet: Deep Embedding Learning for Fine-grained Retrieval, Recognition, and Verification of Microelectronic Images. AIPR 2020: 1-10 - [c97]Shujon Naha, Md. Alimoor Reza, Chen Yu, David J. Crandall:
Localizing Novel Attended Objects in Egocentric Views. BMVC 2020 - [c96]Satoshi Tsutsui, Arjun Chandrasekaran, Md. Alimoor Reza, David J. Crandall, Chen Yu:
A Computational Model of Early Word Learning from the Infant's Point of View. CogSci 2020 - [c95]Shujon Naha, Qingyang Xiao, Prianka Banik, Md. Alimoor Reza, David J. Crandall:
Pose-Guided Knowledge Transfer for Object Part Segmentation. CVPR Workshops 2020: 3961-3955 - [c94]Bardia Doosti, Shujon Naha, Majid Mirbagheri, David J. Crandall:
HOPE-Net: A Graph-Based Model for Hand-Object Pose Estimation. CVPR 2020: 6607-6616 - [c93]Xiankai Lu, Wenguan Wang, Jianbing Shen, Yu-Wing Tai, David J. Crandall, Steven C. H. Hoi:
Learning Video Object Segmentation From Unlabeled Videos. CVPR 2020: 8957-8967 - [c92]Mang Ye, Jianbing Shen, David J. Crandall, Ling Shao, Jiebo Luo:
Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-identification. ECCV (17) 2020: 229-247 - [c91]Ishtiak Zaman, David J. Crandall:
Genetic-GAN: Synthesizing Images Between Two Domains by Genetic Crossover. ECCV Workshops (3) 2020: 312-326 - [c90]David Leake, David J. Crandall:
On Bringing Case-Based Reasoning Methodology to Deep Learning. ICCBR 2020: 343-348 - [c89]Zehua Zhang, Ashish Tawari, Sujitha Martin, David J. Crandall:
Interaction Graphs for Object Importance Estimation in On-road Driving Videos. ICRA 2020: 8920-8927 - [c88]Oluwanisola Ibikunle, John Paden, Maryam Rahnemoonfar, David J. Crandall, Masoud Yari:
Snow Radar Layer Tracking Using Iterative Neural Network Approach. IGARSS 2020: 2960-2963 - [c87]Rakibul Hasan, David J. Crandall, Mario Fritz, Apu Kapadia:
Automatically Detecting Bystanders in Photos to Reduce Privacy Risks. SP 2020: 318-335 - [i38]Wenguan Wang, Xiankai Lu, Jianbing Shen, David J. Crandall, Ling Shao:
Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks. CoRR abs/2001.06807 (2020) - [i37]Xiankai Lu, Wenguan Wang, Jianbing Shen, Yu-Wing Tai, David J. Crandall, Steven C. H. Hoi:
Learning Video Object Segmentation from Unlabeled Videos. CoRR abs/2003.05020 (2020) - [i36]Zehua Zhang, Ashish Tawari, Sujitha Martin, David J. Crandall:
Interaction Graphs for Object Importance Estimation in On-road Driving Videos. CoRR abs/2003.06045 (2020) - [i35]Bardia Doosti, Shujon Naha, Majid Mirbagheri, David J. Crandall:
HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation. CoRR abs/2004.00060 (2020) - [i34]Yu Yao, Xizi Wang, Mingze Xu, Zelin Pu, Ella M. Atkins, David J. Crandall:
When, Where, and What? A New Dataset for Anomaly Detection in Driving Videos. CoRR abs/2004.03044 (2020) - [i33]Satoshi Tsutsui, Arjun Chandrasekaran, Md. Alimoor Reza, David J. Crandall, Chen Yu:
A Computational Model of Early Word Learning from the Infant's Point of View. CoRR abs/2006.02802 (2020) - [i32]Mang Ye, Jianbing Shen, David J. Crandall, Ling Shao, Jiebo Luo:
Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identification. CoRR abs/2007.09314 (2020) - [i31]Yuchen Wang, Mingze Xu, John Paden, Lora Koenig, Geoffrey C. Fox, David J. Crandall:
Deep Tiered Image Segmentation forDetecting Internal Ice Layers in Radar Imagery. CoRR abs/2010.03712 (2020) - [i30]Satoshi Tsutsui, Yanwei Fu, David J. Crandall:
Whose hand is this? Person Identification from Egocentric Hand Gestures. CoRR abs/2011.08900 (2020) - [i29]Zehua Zhang, David Crandall:
Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning. CoRR abs/2011.11261 (2020)
2010 – 2019
- 2019
- [j14]Victor Berger, Mingze Xu, Mohanad Al-Ibadi, Shane Chu, David J. Crandall, John Paden, Geoffrey Charles Fox:
Automated Ice-Bottom Tracking of 2D and 3D Ice Radar Imagery Using Viterbi and TRW-S. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 12(9): 3272-3285 (2019) - [c86]Rakibul Hasan, Yifang Li, Eman T. Hassan, Kelly Caine, David J. Crandall, Roberto Hoyle, Apu Kapadia:
Can Privacy Be Satisfying?: On Improving Viewer Satisfaction for Privacy-Enhanced Photos Using Aesthetic Transforms. CHI 2019: 367 - [c85]Hadar Karmazyn Raz, Drew H. Abney, David J. Crandall, Chen Yu, Linda B. Smith:
How do infants start learning object names in a sea of clutter? CogSci 2019: 521-526 - [c84]Ziyu Xiang, Linda B. Smith, David J. Crandall:
Semantic structure of infant first-person scenes changes with development. CogSci 2019: 3607 - [c83]Jianwei Yang, Zhile Ren, Mingze Xu, Xinlei Chen, David J. Crandall, Devi Parikh, Dhruv Batra:
Embodied Amodal Recognition: Learning to Move to Perceive Objects. ICCV 2019: 2040-2050 - [c82]Mingze Xu, Mingfei Gao, Yi-Ting Chen, Larry Davis, David J. Crandall:
Temporal Recurrent Networks for Online Action Detection. ICCV 2019: 5531-5540 - [c81]Wenguan Wang, Xiankai Lu, Jianbing Shen, David J. Crandall, Ling Shao:
Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks. ICCV 2019: 9235-9244 - [c80]Yu Yao, Mingze Xu, Chiho Choi, David J. Crandall, Ella M. Atkins, Behzad Dariush:
Egocentric Vision-based Future Vehicle Localization for Intelligent Driving Assistance Systems. ICRA 2019: 9711-9717 - [c79]