Publication (by years)
Please see my Google scholar page here.
Selected Publications
ML (18): 7 NeurIPS/NIPS, 8 ICLR, 1 ICML, 1 UAI, 1 KDD
Vision (28): 15 CVPR, 7 ICCV, 3 ECCV, 1 PAMI, 1 IJCV, 1 PR
NLP (3): 2 NAACL, 1 EMNLP
Robotics (7): 2 RA-L, 5 ICRA
AI (1): 1 AAAI
CVPR 2024. "Dual-View Visual Contextualization for Web Navigation." Jihyung Kil, Chan Hee Song, Boyuan Zheng, Xiang Deng, Yu Su, Wei-Lun Chao.
CVPR 2024. "BioCLIP: A Vision Foundation Model for the Tree of Life." Samuel Stevens, Jiaman Wu, Matthew J Thompson, Elizabeth G Campolongo, Chan Hee Song, David Edward Carlyn, Li Dong, Wasila M Dahdul, Charles Stewart, Tanya Berger-Wolf, Wei-Lun Chao, Yu Su
ICLR 2024. "Pre-Training LiDAR-Based 3D Object Detectors Through Colorization." Tai-Yu Pan, Chenyang Ma, Tianle Chen, Cheng Perng Phoo, Katie Z Luo, Yurong You, Mark Campbell, Kilian Q Weinberger, Bharath Hariharan, Wei-Lun Chao.
ICLR 2024. "A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis." Dipanjyoti Paul, Arpita Chowdhury, Xinqi Xiong, Feng-Ju Chang, David Carlyn, Samuel Stevens, Kaiya Provost, Anuj Karpatne, Bryan Carstens, Daniel Rubenstein, Charles Stewart, Tanya Berger-Wolf, Yu Su, Wei-Lun Chao.
ICRA 2024. "Better Monocular 3D Detectors with LiDAR from the Past." Yurong You, Cheng Perng Phoo, Carlos Diaz-Ruiz, Katie Luo, Wei-Lun Chao, Mark Campbell, Bharath Hariharan, Kilian Weinberger
NeurIPS 2023-Workshop. "Making Batch Normalization Great in Federated Deep Learning." Jike Zhong, Hong-You Chen, Wei-Lun Chao
NeurIPS 2023-Workshop. "Segment Anything Model (SAM) Enhances PseudoLabels for Weakly Supervised Semantic Segmentation." Tianle Chen, Zheda Mai, Ruiwen Li, Wei-Lun Chao
NeurIPS 2023. "Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data." Cheng-Hao Tu, Hong-You Chen, Zheda Mai, Jike Zhong, Vardaan Pahuja, Tanya Berger-Wolf, Song Gao, Charles Stewart, Yu Su, Wei-Lun Chao.
ICCV 2023. "Unified Out-Of-Distribution Detection: A Model-Specific Perspective." Muhammad Reza Averly, Wei-Lun Chao
ICCV 2023. "LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models." Chan Hee Song, Jiaman Wu, Clayton Washington, Brian Sadler, Wei-Lun Chao, Yu Su
ICCV 2023. "PreSTU: Pre-Training for Scene-Text Understanding." Jihyung Kil, Soravit Changpinyo, Xi Chen, Hexiang Hu, Sebastian Goodman, Wei-Lun Chao, Radu Soricut
CVPR 2023. "Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning." Cheng-Hao Tu, Zheda Mai, Wei-Lun Chao
CVPR 2023. "Train-Once-for-All Personalization." Hong-You Chen, Yandong Li, Yin Cui, Mingda Zhang, Wei-Lun Chao, Li Zhang
CVPR 2023. "Towards Open-World Segmentation of Parts." Tai-Yu Pan, Qing Liu, Wei-Lun Chao, Brian L. Price
ICLR 2023. "On the Importance and Applicability of Pre-Training for Federated Learning." Hong-You Chen, Cheng-Hao Tu, Ziwei Li, Han Wei Shen, Wei-Lun Chao
ICRA 2023. "Image-to-Image Translation for Autonomous Driving from Coarsely-Aligned Image Pairs." Youya Xia, Josephine Monica, Wei-Lun Chao, Bharath Hariharan, Kilian Q. Weinberger, Mark Campbell
ICRA 2023. "Probabilistic Uncertainty Quantification of Prediction Models with Application to Visual Localization." Junan Chen, Josephine Monica, Wei-Lun Chao, Mark Campbell
AAAI 2023. "Learning Fractals by Gradient Descent." Cheng-Hao Tu, Hong-You Chen, David Carlyn, Wei-Lun Chao
KDD 2023. "Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks." Mohannad Elhamod, Mridul Khurana, Harish Babu Manogaran, Josef C Uyeda, Meghan A Balk, Wasila Dahdul, Yasin Bakış, Henry L Bart Jr, Paula M Mabee, Hilmar Lapp, James P Balhoff, Caleb Charpentier, David Carlyn, Wei-Lun Chao, Charles V Stewart, Daniel I Rubenstein, Tanya Berger-Wolf, Anuj Karpatne
NeurIPS 2022-Workshop. "Understanding Federated Learning through Loss Landscape Visualizations: A Pilot Study." Ziwei Li, Hong-You Chen, Han-Wei Shen, Wei-Lun Chao
NeurIPS 2022. "Unsupervised Adaptation from Repeated Traversals for Autonomous Driving." Yurong You, Cheng Perng Phoo, Katie Z Luo, Travis Zhang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, and Kilian Q Weinberger. [link, pdf, suppl]
ECCV 2022. "Learning with Free Object Segments for Long-Tailed Instance Segmentation." Cheng Zhang, Tai-Yu Pan, Tianle Chen, Jike Zhong, Wenjin Fu, and Wei-Lun Chao. [link, pdf, suppl]
CVPR 2022. "One Step at a Time: Long-Horizon Vision-and-Language Navigation with Milestones." Chan Hee Song, Jihyung Kil, Tai-Yu Pan, Brian Sadler, Wei-Lun Chao, and Yu Su. [link, pdf, suppl]
CVPR 2022. "Learning to Detect Mobile Objects from LiDAR Scans Without Labels." Yurong You, Katie Luo, Cheng Perng Phoo, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark Campbell, and Kilian Weinberger. [link, pdf, suppl, code]
CVPR 2022. "Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions." Carlos Diaz-Ruiz, Youya Xia, Yurong You, Jose Nino, Junan Chen, Josephine Monica, Xiangyu Chen, Katie Luo, Yan Wang, Marc Emond, Wei-Lun Chao, Bharath Hariharan, Kilian Weinberger, and Mark Campbell. [link, pdf, suppl, data]
ICLR 2022. "On Bridging Generic and Personalized Federated Learning for Image Classification." Hong-You Chen and Wei-Lun Chao. [link, pdf]
ICLR 2022. "How to Train Your MAML to Excel in Few-Shot Classification." Han-Jia Ye and Wei-Lun Chao. [link, pdf, code]
ICLR 2022. "Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception." Yurong You, Katie Z Luo, Xiangyu Chen, Junan Chen, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark Campbell, and Kilian Q Weinberger. [link, pdf, code]
ICRA 2022. "Sequential Joint Shape and Pose Estimation of Vehicles with Application to Automatic Amodal Segmentation Labeling" Josephine Monica, Wei-Lun Chao, and Mark Campbell. [link, pdf]
ICRA 2022. "Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection." Yurong You, Carlos Andres Diaz-Ruiz, Yan Wang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, Kilian Q Weinberger. [link, pdf]
PAMI 2022. "Few-Shot Learning with a Strong Teacher." Han-Jia Ye, Lu Ming, De-Chuan Zhan, and Wei-Lun Chao. [link, pdf, code]
NeurIPS 2021. "Gradual Domain Adaptation without Indexed Intermediate Domains." Hong-You Chen and Wei-Lun Chao. [link, pdf, suppl]
NeurIPS 2021. "On Model Calibration for Long-Tailed Object Detection and Instance Segmentation." Tai-Yu Pan, Cheng Zhang, Yandong Li, Hexiang Hu, Dong Xuan, Soravit Changpinyo, Boqing Gong, and Wei-Lun Chao. [link, pdf, suppl]
EMNLP 2021. "Discovering the Unknown Knowns: Turning Implicit Knowledge in the Dataset into Explicit Training Examples for Visual Question Answering." Jihyung Kil, Cheng Zhang, Dong Xuan, and Wei-Lun Chao.
ICCV 2021. "Procrustean Training for Imbalanced Deep Learning." Han-Jia Ye, De-Chuan Zhan, and Wei-Lun Chao.
ICCV 2021. "MosaicOS: A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection." Cheng Zhang, Tai-Yu Pan, Yandong Li, Hexiang Hu, Dong Xuan, Soravit Changpinyo, Boqing Gong, and Wei-Lun Chao.
ICCV 2021. "Deep Co-Training with Task Decomposition for Semi-Supervised Domain Adaptation." Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, and Ser-Nam Lim.
NAACL 2021. "Revisiting Document Representations for Large-Scale Zero-Shot Learning." Jihyung Kil and Wei-Lun Chao.
ICLR 2021. "FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning." Hong-You Chen and Wei-Lun Chao. (A preliminary version won the best student paper in SpicyFL 2020: NeurIPS Workshop on Scalability, Privacy, and Security in Federated Learning)
Gastrointestinal Endoscopy 2021. "High performance in risk stratification of intraductal papillary mucinous neoplasms by confocal laser endomicroscopy image analysis with convolutional neural networks (with video)." Jorge D. Machicado, Wei-Lun Chao, David E. Carlyn, Tai-Yu Pan, Sarah Poland, Victoria L. Alexander, Tassiana G. Maloof et al.
NeurIPS 2020. "Wasserstein Distances for Stereo Disparity Estimation." Divyansh Garg, Yan Wang, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, and Wei-Lun Chao.
CVPR 2020. "Train in Germany, Test in the USA: Making 3D Object Detectors Generalize." Yan Wang*, Xiangyu Chen*, Yurong You*, Li Erran Li, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, and Wei-Lun Chao.
CVPR 2020. "End-to-end Pseudo-LiDAR for Image-Based 3D Object Detection." Rui Qian*, Divyansh Garg*, Yan Wang, Yurong You, Serge Belongie, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, and Wei-Lun Chao.
ICLR 2020. "Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving." Yurong You*, Yan Wang*, Wei-Lun Chao*, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark Campbell, and Kilian Q. Weinberger.
WACV 2020. "Visual Question Answering on 360 Images." Shih-Han Chou, Wei-Lun Chao, Wei-Sheng Lai, Min Sun, and Ming-Hsuan Yang.
RA-L 2020. "Interactive Natural Language-based Person Search." Vikram Shree, Wei-Lun Chao, and Mark Campbell.
IJCV 2020. "Classifier and Exemplar Synthesis for Zero-Shot Learning." Soravit Changpinyo*, Wei-Lun Chao*, Boqing Gong, and Fei Sha.
arXiv 2020. "Revisiting Meta-Learning as Supervised Learning." Wei-Lun Chao*, Han-Jia Ye*, De-Chuan Zhan, Mark Campbell, and Kilian Q. Weinberger.
arXiv 2020. "Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning." Han-Jia Ye, Hong-You Chen, De-Chuan Zhan, and Wei-Lun Chao.
NeurIPS 2019. "A New Defense Against Adversarial Images: Turning a Weakness into a Strength." Shengyuan Hu, Tao Yu, Chuan Guo, Wei-Lun Chao, and Kilian Q. Weinberger.
CVPR 2019. "Pseudo-LiDAR from visual depth estimation: bridging the gap in 3D object detection for autonomous driving." Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark Campbell, and Kilian Q. Weinberger.
BMVC, 2019. "An Empirical Study on Leveraging Scene Graphs for Visual Question Answering." Cheng Zhang, Wei-Lun Chao, and Dong Xuan.
RA-L 2019. "LDLS: 3D Object Segmentation through Label Diffusion from 2D Images." Brian Wang, Wei-Lun Chao, Yan Wang, Bharath Hariharan, Kilian Q. Weinberger, and Mark Campbell.
arXiv 2019 (cited > 200 times). "SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning." Yan Wang, Wei-Lun Chao, Kilian Q Weinberger, and Laurens van der Maaten.
CVPR 2018. "Cross-dataset adaptation for visual question answering." Wei-Lun Chao*, Hexiang Hu*, and Fei Sha.
CVPR 2018. "Learning answer embeddings for visual question answering." Hexiang Hu*, Wei-Lun Chao*, and Fei Sha.
NAACL 2018. "Being negative but constructively: lessons learnt from creating better visual question answering datasets." Wei-Lun Chao*, Hexiang Hu*, and Fei Sha.
ICCV 2017. "Predicting visual exemplars of unseen classes for zero-shot learning." Soravit Changpinyo, Wei-Lun Chao, and Fei Sha.
ECCV 2016. "An empirical study and analysis of generalized zero-Shot learning for object recognition in the wild." Wei-Lun Chao*, Soravit Changpinyo*, Boqing Gong, and Fei Sha.
ECCV 2016. "Video summarization with long short-term memory." Ke Zhang*, Wei-Lun Chao*, Fei Sha, and Kristen Grauman.
CVPR 2016. "Synthesized classifiers for zero-shot learning." Soravit Changpinyo*, Wei-Lun Chao*, Boqing Gong, and Fei Sha.
CVPR 2016. "Summary transfer: exemplar-based subset selection for video summarization." Ke Zhang*, Wei-Lun Chao*, Fei Sha, and Kristen Grauman.
UAI 2015. "Large-margin determinantal point processes." Wei-Lun Chao*, Boqing Gong*, Kristen Grauman, and Fei Sha.
ICML 2015. "Exponential Integration for Hamiltonian Monte Carlo." Wei-Lun Chao, Justin Solomon, Dominik Michels, and Fei Sha.
Signal Processing 2015. "Facial expression recognition based on improved local binary pattern and class-regularized locality preserving projection." Wei-Lun Chao, Jian-Jiun Ding, Jun-Zuo Liu.
NIPS 2014. "Diverse sequential subset selection for supervised video summarization." Boqing Gong*, Wei-Lun Chao*, Kristen Grauman, and Fei Sha.
Pattern Recognition 2013. "Facial age estimation based on label-sensitive learning and age-oriented regression." Wei-Lun Chao, Jun-Zuo Liu, and Jian-Jiun Ding.