Publication (by topics)

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

Perception for Autonomous Driving

• 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. 

• 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

• 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

• 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. "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]

• 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. "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. 

• 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. 

• 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. 

Learning with Imperfect Data

Domain Adaptation

• 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. 

• 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]

• 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]

• NeurIPS 2021. "Gradual Domain Adaptation without Indexed Intermediate Domains." Hong-You Chen and Wei-Lun Chao. [link, pdf, suppl]

• 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. 

• 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 2018. "Cross-dataset adaptation for visual question answering." Wei-Lun Chao*, Hexiang Hu*, and Fei Sha. 

Imbalanced Learning

• 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]

• 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]

• 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. 

• 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.

Meta-Learning and Few-Shot Learning

• 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

• ICLR 2022. "How to Train Your MAML to Excel in Few-Shot Classification." Han-Jia Ye and Wei-Lun Chao. [link, pdf, code]

• PAMI 2022. "Few-Shot Learning with a Strong Teacher." Han-Jia Ye, Lu Ming, De-Chuan Zhan, and Wei-Lun Chao. [link, pdf, code]

• arXiv 2020. "Revisiting Meta-Learning as Supervised Learning." Wei-Lun Chao*, Han-Jia Ye*, De-Chuan Zhan, Mark Campbell, and Kilian Q. Weinberger. 

• 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. 

Zero-Shot Learning

• CVPR 2023. "Towards Open-World Segmentation of Parts." Tai-Yu Pan, Qing Liu, Wei-Lun Chao, Brian L. Price

• NAACL 2021. "Revisiting Document Representations for Large-Scale Zero-Shot Learning." Jihyung Kil and Wei-Lun Chao. 

• IJCV 2020. "Classifier and Exemplar Synthesis for Zero-Shot Learning." Soravit Changpinyo*, Wei-Lun Chao*, Boqing Gong, 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. 

• CVPR 2016. "Synthesized classifiers for zero-shot learning." Soravit Changpinyo*, Wei-Lun Chao*, Boqing Gong, and Fei Sha. 

Federated Learning

• NeurIPS 2023-Workshop. "Making Batch Normalization Great in Federated Deep Learning." Jike Zhong, Hong-You Chen, Wei-Lun Chao

• 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

• NeurIPS 2022-Workshop. "Understanding Federated Learning through Loss Landscape Visualizations: A Pilot Study." Ziwei Li, Hong-You Chen, Han-Wei Shen, Wei-Lun Chao

• ICLR 2022. "On Bridging Generic and Personalized Federated Learning for Image Classification." Hong-You Chen and Wei-Lun Chao. [link, pdf]

• 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)

Personalization

• CVPR 2023. "Train-Once-for-All Personalization." Hong-You Chen, Yandong Li, Yin Cui, Mingda Zhang, Wei-Lun Chao, Li Zhang

OOD detection

• ICCV 2023. "Unified Out-Of-Distribution Detection: A Model-Specific Perspective." Muhammad Reza Averly, Wei-Lun Chao

Weakly-Supervised Learning

• NeurIPS 2023-Workshop. "Segment Anything Model (SAM) Enhances PseudoLabels for Weakly Supervised Semantic Segmentation." Tianle Chen, Zheda Mai, Ruiwen Li, Wei-Lun Chao

ML for Imageomics (ML meets Biology)

• 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.

• 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

• 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 

Vision and Language

• CVPR 2024. "Dual-View Visual Contextualization for Web Navigation." Jihyung Kil, Chan Hee Song, Boyuan Zheng, Xiang Deng, Yu Su, 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 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]

• 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. 

• 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. 

• BMVC, 2019. "An Empirical Study on Leveraging Scene Graphs for Visual Question Answering." Cheng Zhang, Wei-Lun Chao, and Dong Xuan. 

• 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. 

Health Care

• 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. 

Video Summarization

• ECCV 2016. "Video summarization with long short-term memory." Ke Zhang*, Wei-Lun Chao*, Fei Sha, and Kristen Grauman. 

• 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. 

• NIPS 2014. "Diverse sequential subset selection for supervised video summarization." Boqing Gong*, Wei-Lun Chao*, Kristen Grauman, and Fei Sha. 

Others

• AAAI 2023. "Learning Fractals by Gradient Descent." Cheng-Hao Tu, Hong-You Chen, David Carlyn, 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. 

• 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. 

• 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.