Kevin J. Liang

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 43

Top Topics

Feature Distributions

Bayesian Nonparametric

Text Recognition

Top Venues

Publications

Vinay Kumar Verma, Nikhil Mehta, Kevin J. Liang, Aakansha Mishra, Lawrence Carin
Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning. WACV (2024)
Nikhil Mehta, Kevin J. Liang, Jing Huang, Fu-Jen Chu, Li Yin, Tal Hassner
HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings. WACV (2024)
Weiyao Wang, Pierre Gleize, Hao Tang, Xingyu Chen, Kevin J. Liang, Matt Feiszli
ICON: Incremental CONfidence for Joint Pose and Radiance Field Optimization. CoRR (2024)
Peri Akiva, Jing Huang, Kevin J. Liang, Rama Kovvuri, Xingyu Chen, Matt Feiszli, Kristin J. Dana, Tal Hassner
Self-Supervised Object Detection from Egocentric Videos. ICCV (2023)
Nikhil Mehta, Kevin J. Liang, Jing Huang, Fu-Jen Chu, Li Yin, Tal Hassner
HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings. CoRR (2023)
Vinay Kumar Verma, Nikhil Mehta, Kevin J. Liang, Aakansha Mishra, Lawrence Carin
Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning. CoRR (2023)
Samrudhdhi B. Rangrej, Kevin J. Liang, Tal Hassner, James J. Clark
GliTr: Glimpse Transformers with Spatiotemporal Consistency for Online Action Prediction. WACV (2023)
Kristen Grauman, Andrew Westbury, Lorenzo Torresani, Kris Kitani, Jitendra Malik, Triantafyllos Afouras, Kumar Ashutosh, Vijay Baiyya, Siddhant Bansal, Bikram Boote, Eugene Byrne, Zachary Chavis, Joya Chen, Feng Cheng, Fu-Jen Chu, Sean Crane, Avijit Dasgupta, Jing Dong, María Escobar, Cristhian Forigua, Abrham Gebreselasie, Sanjay Haresh, Jing Huang, Md Mohaiminul Islam, Suyog Dutt Jain, Rawal Khirodkar, Devansh Kukreja, Kevin J. Liang, Jia-Wei Liu, Sagnik Majumder, Yongsen Mao, Miguel Martin, Effrosyni Mavroudi, Tushar Nagarajan, Francesco Ragusa, Santhosh Kumar Ramakrishnan, Luigi Seminara, Arjun Somayazulu, Yale Song, Shan Su, Zihui Xue, Edward Zhang, Jinxu Zhang, Angela Castillo, Changan Chen, Xinzhu Fu, Ryosuke Furuta, Cristina González, Prince Gupta, Jiabo Hu, Yifei Huang, Yiming Huang, Weslie Khoo, et al.
Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives. CoRR (2023)
Hao Tang, Kevin J. Liang, Kristen Grauman, Matt Feiszli, Weiyao Wang
EgoTracks: A Long-term Egocentric Visual Object Tracking Dataset. NeurIPS (2023)
Li Yin, Juan M. Perez-Rua, Kevin J. Liang
Sylph: A Hypernetwork Framework for Incremental Few-shot Object Detection. CVPR (2022)
Li Yin, Juan M. Perez-Rua, Kevin J. Liang
Sylph: A Hypernetwork Framework for Incremental Few-shot Object Detection. CoRR (2022)
Weituo Hao, Nikhil Mehta, Kevin J. Liang, Pengyu Cheng, Mostafa El-Khamy, Lawrence Carin
WAFFLe: Weight Anonymized Factorization for Federated Learning. IEEE Access 10 (2022)
Kevin J. Liang, Samrudhdhi B. Rangrej, Vladan Petrovic, Tal Hassner
Few-shot Learning with Noisy Labels. CVPR (2022)
Kevin J. Liang, Samrudhdhi B. Rangrej, Vladan Petrovic, Tal Hassner
Few-shot Learning with Noisy Labels. CoRR (2022)
Jing Huang, Kevin J. Liang, Rama Kovvuri, Tal Hassner
Task Grouping for Multilingual Text Recognition. ECCV Workshops (4) (2022)
Jing Huang, Kevin J. Liang, Rama Kovvuri, Tal Hassner
Task Grouping for Multilingual Text Recognition. CoRR (2022)
Samrudhdhi B. Rangrej, Kevin J. Liang, Tal Hassner, James J. Clark
GliTr: Glimpse Transformers with Spatiotemporal Consistency for Online Action Prediction. CoRR (2022)
Sachin Konan, Kevin J. Liang, Li Yin
Extending One-Stage Detection with Open-World Proposals. CoRR (2022)
Nikhil Mehta, Kevin J. Liang, Vinay Kumar Verma, Lawrence Carin
Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors. AISTATS (2021)
Nathan Inkawhich, Kevin J. Liang, Jingyang Zhang, Huanrui Yang, Hai Li, Yiran Chen
Can Targeted Adversarial Examples Transfer When the Source and Target Models Have No Label Space Overlap? ICCVW (2021)
Jing Huang, Guan Pang, Rama Kovvuri, Mandy Toh, Kevin J. Liang, Praveen Krishnan, Xi Yin, Tal Hassner
A Multiplexed Network for End-to-End, Multilingual OCR. CVPR (2021)
Weituo Hao, Mostafa El-Khamy, Jungwon Lee, Jianyi Zhang, Kevin J. Liang, Changyou Chen, Lawrence Carin
Towards Fair Federated Learning With Zero-Shot Data Augmentation. CVPR Workshops (2021)
Weituo Hao, Mostafa El-Khamy, Jungwon Lee, Jianyi Zhang, Kevin J. Liang, Changyou Chen, Lawrence Carin
Towards Fair Federated Learning with Zero-Shot Data Augmentation. CoRR (2021)
Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Lawrence Carin
Meta-Learned Attribute Self-Gating for Continual Generalized Zero-Shot Learning. CoRR (2021)
Jing Huang, Guan Pang, Rama Kovvuri, Mandy Toh, Kevin J. Liang, Praveen Krishnan, Xi Yin, Tal Hassner
A Multiplexed Network for End-to-End, Multilingual OCR. CoRR (2021)
Nathan Inkawhich, Kevin J. Liang, Jingyang Zhang, Huanrui Yang, Hai Li, Yiran Chen
Can Targeted Adversarial Examples Transfer When the Source and Target Models Have No Label Space Overlap? CoRR (2021)
Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin
Efficient Feature Transformations for Discriminative and Generative Continual Learning. CVPR (2021)
Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin
Efficient Feature Transformations for Discriminative and Generative Continual Learning. CoRR (2021)
Kevin J. Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin
MixKD: Towards Efficient Distillation of Large-scale Language Models. ICLR (2021)
Yuewei Yang, Kevin J. Liang, Lawrence Carin
Object Detection as a Positive-Unlabeled Problem. CoRR (2020)
Yuewei Yang, Kevin J. Liang, Lawrence Carin
Object Detection as a Positive-Unlabeled Problem. BMVC (2020)
Kevin J. Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin
MixKD: Towards Efficient Distillation of Large-scale Language Models. CoRR (2020)
Nathan Inkawhich, Kevin J. Liang, Binghui Wang, Matthew Inkawhich, Lawrence Carin, Yiran Chen
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability. NeurIPS (2020)
Nathan Inkawhich, Kevin J. Liang, Lawrence Carin, Yiran Chen
Transferable Perturbations of Deep Feature Distributions. ICLR (2020)
John B. Sigman, Gregory P. Spell, Kevin J. Liang, Lawrence Carin
Background Adaptive Faster R-CNN for Semi-Supervised Convolutional Object Detection of Threats in X-Ray Images. CoRR (2020)
Nikhil Mehta, Kevin J. Liang, Lawrence Carin
Bayesian Nonparametric Weight Factorization for Continual Learning. CoRR (2020)
Nathan Inkawhich, Kevin J. Liang, Lawrence Carin, Yiran Chen
Transferable Perturbations of Deep Feature Distributions. CoRR (2020)
Weituo Hao, Nikhil Mehta, Kevin J. Liang, Pengyu Cheng, Mostafa El-Khamy, Lawrence Carin
WAFFLe: Weight Anonymized Factorization for Federated Learning. CoRR (2020)
Nathan Inkawhich, Kevin J. Liang, Binghui Wang, Matthew Inkawhich, Lawrence Carin, Yiran Chen
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability. CoRR (2020)
Kevin J. Liang, John B. Sigman, Gregory P. Spell, Dan Strellis, William Chang, Felix Liu, Tejas Mehta, Lawrence Carin
Toward Automatic Threat Recognition for Airport X-ray Baggage Screening with Deep Convolutional Object Detection. CoRR (2019)
Kevin J. Liang, Guoyin Wang, Yitong Li, Ricardo Henao, Lawrence Carin
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods. CoRR (2019)
Kevin J. Liang, Guoyin Wang, Yitong Li, Ricardo Henao, Lawrence Carin
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods. NeurIPS (2019)
Kevin J. Liang, Chunyuan Li, Guoyin Wang, Lawrence Carin
Generative Adversarial Network Training is a Continual Learning Problem. CoRR (2018)