2025

AAAI

Beyond Accuracy: On the Effects of Fine-tuning Towards Vision-Language Model's Prediction Rationality

[AAAI’25] Qitong Wang, Tang Li, Kien X. Nguyen, Xi Peng.

In Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI), 2025. (acceptance rate 23.4%)

Paper

AAAI

Interpretable Failure Detection with Human-Level Concepts

[AAAI’25] Kien X. Nguyen, Tang Li, Xi Peng.

In Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI), 2025. (acceptance rate 23.4%)

Paper

2024

NeurIPS

Beyond Accuracy: Ensuring Correct Predictions with Correct Rationales

[NeurIPS’24] Tang Li, Mengmeng Ma, and Xi Peng.

In Proceedings of the Annual Conference on Neural Information Processing Systems (NeurIPS), 2024. (acceptance rate 25.8%)

PaperCode
@inproceedings{ma2024beyond,
 title={Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients},
 author={Ma, Mengmeng and Li, Tang and Peng, Xi},
 booktitle={Proceedings of the International Conference on Machine Learning (ICML)},
 year={2024}
}

NeurIPS

SeafloorAI: A Large-scale Vision-Language Dataset for Seafloor Geological Survey

[NeurIPS’24] Kien X. Nguyen, Arthur Trembanis, and Xi Peng.

In Proceedings of the Annual Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2024. (acceptance rate 25.3%)

PaperDataset
@inproceedings{ma2024beyond,
 title={Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients},
 author={Ma, Mengmeng and Li, Tang and Peng, Xi},
 booktitle={Proceedings of the International Conference on Machine Learning (ICML)},
 year={2024}
}

ICML

Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients

[ICML'24] Mengmeng Ma, Tang Li, and Xi Peng.

In Proceedings of the International Conference on Machine Learning, 2024. (acceptance rate 27.5%)

PaperCode
@inproceedings{ma2024beyond,
 title={Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients},
 author={Ma, Mengmeng and Li, Tang and Peng, Xi},
 booktitle={Proceedings of the International Conference on Machine Learning (ICML)},
 year={2024}
}

ICML

Ensemble Pruning for Out-of-distribution Generalization

[ICML'24] Fengchun Qiao and Xi Peng.

In Proceedings of the International Conference on Machine Learning, 2024. (acceptance rate 27.5%)

PaperCode
@inproceedings{qiao2024ensemble,
 title={Ensemble Pruning for Out-of-distribution Generalization},
 author={Qiao, Fengchun and Peng, Xi},
 booktitle={Proceedings of the International Conference on Machine Learning (ICML)},
 year={2024}
}

ECCV

DEAL: Disentangle and Localize Concept-level Explanations for VLMs

[ECCV'24 Strong Double Blind] Tang Li, Mengmeng Ma, and Xi Peng.

In Proceedings of the European Conference on Computer Vision, 2024. (acceptance rate 4.5%)

PaperVideoCode
@inproceedings{li2024deal,
 title={DEAL: Disentangle and Localize Concept-level Explanations for VLMs},
 author={Li, Tang and Ma, Mengmeng and Peng, Xi},
 booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
 year={2024}
}

CIKM

Adaptive Cascading Network for Continual Test-Time Adaptation

[CIKM'24] Kien X. Nguyen*, Fengchun Qiao*, and Xi Peng.

In Proceedings of the Conference on Information and Knowledge Management (CIKM) 2024. (acceptance rate 23%)

Paper
@inproceedings{li2024deal,
 title={DEAL: Disentangle and Localize Concept-level Explanations for VLMs},
 author={Li, Tang and Ma, Mengmeng and Peng, Xi},
 booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
 year={2024}
}

2023

ICLR

Topology-aware Robust Optimization for Out-of-Distribution Generalization

[ICLR'23] Fengchun Qiao and Xi Peng.

In Proceedings of the International Conference on Learning Representations, 2023. (acceptance rate 31.8%)

PaperCode
@inproceedings{qiao2023topology,
 title={Topology-aware Robust Optimization for Out-of-Distribution Generalization},
 author={Qiao, Fengchun and Peng, Xi},
 booktitle={Proceedings of the International Conference on Learning Representations (ICLR)},
 year={2023}
}

CVPR

Are Data-driven Explanations Robust against Out-of-distribution Data?

[CVPR'23] Tang Li, Fengchun Qiao, Mengmeng Ma, and Xi Peng.

In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2023. (acceptance rate 25.8%)

PaperVideoCode
@inproceedings{li2023data,
 title={Are Data-driven Explanations Robust against Out-of-distribution Data?},
 author={Li, Tang and Qiao, Fengchun and Ma, Mengmeng and Peng, Xi},
 booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
 pages={3821--3831},
 year={2023}
}

ICCV

Learning from Semantic Alignment between Unpaired Multiviews for Egocentric Video Recognition

[ICCV'23] Qitong Wang, Long Zhao, Liangzhe Yuan, Ting Liu, and Xi Peng.

In Proceedings of IEEE International Conference on Computer Vision (ICCV) 2023. (acceptance rate 26.8%)

PaperCode
@inproceedings{Wang2023LearningFS,
 title={Learning from Semantic Alignment between Unpaired Multiviews for Egocentric Video Recognition},
 author={Qitong Wang and Long Zhao and Liangzhe Yuan and Ting Liu and Xi Peng},
 booktitle={Proceedings of the International Conference on Computer Vision (ICCV)},
 year={2023},
 url={https://api.semanticscholar.org/CorpusID:261064926}}
}

CVIU

Deep learning-based estimation of whole-body kinematics from multi-view images

[CVIU'23] Kien X. Nguyen, Liying Zheng, Ashley L. Hawke, Robert E. Carey, Scott P. Breloff, Kang Li, and Xi Peng.

Computer Vision and Image Understanding, 2023. (impact factor 4.9)

PaperCode
@article{nguyen2023deep,
 title={Deep learning-based estimation of whole-body kinematics from multi-view images},
 author={Nguyen, Kien X and Zheng, Liying and Hawke, Ashley L and Carey, Robert E and Breloff, Scott P and Li, Kang and Peng, Xi},
 journal={Computer Vision and Image Understanding},
 volume={235},
 pages={103780},
 year={2023},
 publisher={Elsevier}
}

TNNLS

Semi-identical Twins Variational AutoEncoder for Few-Shot Learning

[TNNLS'23] Yi Zhang, Sheng Huang, Xi Peng, Dan Yang.

IEEE Transactions on Neural Networks and Learning Systems, 2023. (impact factor 14.26)

Paper
@article{nguyen2023deep,
 title={Deep learning-based estimation of whole-body kinematics from multi-view images},
 author={Nguyen, Kien X and Zheng, Liying and Hawke, Ashley L and Carey, Robert E and Breloff, Scott P and Li, Kang and Peng, Xi},
 journal={Computer Vision and Image Understanding},
 volume={235},
 pages={103780},
 year={2023},
 publisher={Elsevier}
}

TN

Adapting Wireless Network Configuration From Simulation to Reality via Deep Learning-Based Domain Adaptation

[TN'23] Junyang Shi, Aitian Ma, Xia Cheng, Mo Sha, Xi Peng.

IEEE/ACM Transactions on Networking, 2023. (impact factor 3.9)

Paper
@article{nguyen2023deep,
 title={Deep learning-based estimation of whole-body kinematics from multi-view images},
 author={Nguyen, Kien X and Zheng, Liying and Hawke, Ashley L and Carey, Robert E and Breloff, Scott P and Li, Kang and Peng, Xi},
 journal={Computer Vision and Image Understanding},
 volume={235},
 pages={103780},
 year={2023},
 publisher={Elsevier}
}

2022

TPAMI

Out-of-Domain Generalization from a Single Source: An Uncertainty Quantification Approach

[TPAMI'22, IF=24.3] Xi Peng, Fengchun Qiao, and Long Zhao.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022. (impact factor 24.3)

Paper

@article{peng2022out,
 title={Out-of-Domain Generalization From a Single Source: An Uncertainty Quantification Approach},
 author={Peng, Xi and Qiao, Fengchun and Zhao, Long},
 journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
 year={2022},
 publisher={IEEE}
}

CVPR

Are Multimodal Transformers Robust to Missing Modality?

[CVPR'22] Mengmeng Ma, Jian Ren, Long Zhao, Davide Testuggine, and Xi Peng.

In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2022. (acceptance rate 25.3%)

PaperVideo

@inproceedings{ma2022multimodal,
 title={Are Multimodal Transformers Robust to Missing Modality?},
 author={Ma, Mengmeng and Ren, Jian and Zhao, Long and Testuggine, Davide and Peng, Xi},
 booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
 pages={18177--18186},
 year={2022}
}

CVPR

Symmetry and Uncertainty-Aware Object SLAM for 6DoF Object Pose Estimation

[CVPR'22] Nathaniel Merrill, Yuliang Guo, Xingxing Zuo, Xinyu Huang, Stefan Leutenegger, Xi Peng, Liu Ren, and Guoquan Huang.

In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2022. (acceptance rate 25.3%)

Paper

@inproceedings{merrill2022symmetry,
 title={Symmetry and Uncertainty-Aware Object SLAM for 6DoF Object Pose Estimation},
 author={Merrill, Nathaniel and Guo, Yuliang and Zuo, Xingxing and Huang, Xinyu and Leutenegger, Stefan and Peng, Xi and Ren, Liu and Huang, Guoquan},
 booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
 pages={14901--14910},
 year={2022}
}

TMM

Region-aware Arbitrary-shaped Text Detection with Progressive Fusion

[TMM'22, IF=8.18] Qitong Wang, Bin Fu, Ming Li, Junjun He, Xi Peng, Yu Qiao.

IEEE Transactions on Multimedia, 2022.

Paper

@article{wang2022region,
 title={Region-aware Arbitrary-shaped Text Detection with Progressive Fusion},
 author={Wang, Qitong and Fu, Bin and Li, Ming and He, Junjun and Peng, Xi and Qiao, Yu},
 journal={IEEE Transactions on Multimedia},
 year={2022},
 publisher={IEEE}
}

NeurIPS

Graph-Relational Distributionally Robust Optimization

[NeurIPS'22W] Fengchun Qiao, Xi Peng.

In Proceedings of the 36th Conference on Neural Information Processing Systems Workshops.

PaperVideo

@inproceedings{qiao2022graph,
 title={Graph-Relational Distributionally Robust Optimization},
 author={Qiao, Fengchun and Peng, Xi},
 booktitle={NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and Applications}
}

WACV

Self-Guidance: Improve Deep Neural Network Generalization via Knowledge Distillation

[WACV'22] Zhenzhu Zheng* and Xi Peng.

In IEEE Winter Conference on Applications of Computer Vision, 2022.

Paper

@inproceedings{qiao2022graph,
 title={Graph-Relational Distributionally Robust Optimization},
 author={Qiao, Fengchun and Peng, Xi},
 booktitle={NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and Applications}
}

CMBBE

Video-based 3D Poste Estimation for Residential Roofing

[CMBBE'22] Ruochen Wang*, Liyang Zheng, Ashley L. Hawke, Robert E. Carey, Scott P. Breloff, Kang Li, Xi Peng.

Computer Methods in Biomechanics and Biomedical Engineering, 2022.

Paper

@inproceedings{qiao2022graph,
 title={Graph-Relational Distributionally Robust Optimization},
 author={Qiao, Fengchun and Peng, Xi},
 booktitle={NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and Applications}
}

2021

NeurIPS

Deep Learning for Spatiotemporal Modeling of Urbanization

[NeurIPS'21W Best Paper Award] Tang Li, Jing Gao, and Xi Peng. 

Accepted & Best Paper Awarded by NeurIPS 2021 Machine Learning in Public Health Workshop.

PaperVideoPress

@article{li2021deep,
title={Deep Learning for Spatiotemporal Modeling of Urbanization},
author={Tang Li and Gao, Jing and Xi Peng},
journal={Advances in Neural Information Processing Systems Workshops (Best Paper Award)},
year={2021}
}

ICLR

A Good Image Generator Is What You Need for High-Resolution Video Synthesis

[ICLR'21 Spotlight] Yu Tian, Jian Ren, Menglei Chai, Kyle Olszewski, Xi Peng, Dimitris N. Metaxas, Sergey Tulyakov.

In Proceedings of the International Conference on Learning Representations, 2021. (acceptance rate 3.80%)

PaperVideo

@inproceedings{tian2020good,
 title={A Good Image Generator Is What You Need for High-Resolution Video Synthesis},
 author={Tian, Yu and Ren, Jian and Chai, Menglei and Olszewski, Kyle and Peng, Xi and Metaxas, Dimitris N and Tulyakov, Sergey},
 booktitle={International Conference on Learning Representations},
 year={2020}
}

CVPR

Learning View-Disentangled Human Pose Representation by Contrastive Cross-View Mutual Information Maximization

[CVPR'21 Oral] Long Zhao, Yuxiao Wang, Jiaping Zhao, Liangzhe Yuan, Jennifer J Sun, Florian Schroff, Hartwig Adam, Xi Peng, Dimitris Metaxas, Ting Liu.

In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021. (acceptance rate 4.3%)

PaperVideo

@inproceedings{zhao2021learning,
 title={Learning view-disentangled human pose representation by contrastive cross-view mutual information maximization},
 author={Zhao, Long and Wang, Yuxiao and Zhao, Jiaping and Yuan, Liangzhe and Sun, Jennifer J and Schroff, Florian and Adam, Hartwig and Peng, Xi and Metaxas, Dimitris and Liu, Ting},
 booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
 pages={12793--12802},
 year={2021}
}

CVPR

Uncertainty-guided Model Generalization to Unseen Domains

[CVPR'21] Fengchun Qiao and Xi Peng. 

In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021. (acceptance rate 23.4%)

PaperVideo

@inproceedings{qiao2021uncertainty,
 title={Uncertainty-guided model generalization to unseen domains},
 author={Qiao, Fengchun and Peng, Xi},
 booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
 pages={6790--6800},
 year={2021}
}

AAAI

SMIL: Multimodal Learning with Severely Missing Modality

[AAAI'21] Mengmeng Ma, Jian Ren, Long Zhao, Sergey Tulyakov, Cathy Wu, Xi Peng.

In Proceedings of the Association for the Advancement of Artificial Intelligence, 2020. (acceptance rate 21%)

PaperCodeVideoVideo - 15min

@inproceedings{ma2021smil,
 title={SMIL: Multimodal learning with severely missing modality},
 author={Ma, Mengmeng and Ren, Jian and Zhao, Long and Tulyakov, Sergey and Wu, Cathy and Peng, Xi},
 booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
 volume={35},
 number={3},
 pages={2302--2310},
 year={2021}
}

NSDI

Adapting Wireless Mesh Network Configuration from Simulation to Reality via Deep Learning based Domain Adaptation

[NSDI'21] Junyang Shi, Mo Sha, Xi Peng.

In Proceedings of USENIX Symposium on Networked Systems Design and Implementation, 2021.

Paper

@inproceedings{shi2021adapting,
 title={Adapting wireless mesh network configuration from simulation to reality via deep learning based domain adaptation},
 author={Shi, Junyang and Sha, Mo and Peng, Xi},
 booktitle={18th USENIX Symposium on Networked Systems Design and Implementation (NSDI 21)},
 pages={887--901},
 year={2021}
}

BIBM

Understanding the Factors Related to the Opioid Epidemic using Machine Learning

[BIBM'21] Sachin Gavali, Chuming Chen, Julie Cowart, Xi Peng, Shanshan Ding, Cathy Wu, Tammy Anderson.

In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021.

Paper

@inproceedings{shi2021adapting,
 title={Adapting wireless mesh network configuration from simulation to reality via deep learning based domain adaptation},
 author={Shi, Junyang and Sha, Mo and Peng, Xi},
 booktitle={18th USENIX Symposium on Networked Systems Design and Implementation (NSDI 21)},
 pages={887--901},
 year={2021}
}

2020

CVPR

Learning to Learn Single Domain Generalization

[CVPR'20] Fengchun Qiao, Long Zhao, and Xi Peng.

In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2020. (acceptance rate 22%)

Paper

@inproceedings{qiao2020learning,
 title={Learning to learn single domain generalization},
 author={Qiao, Fengchun and Zhao, Long and Peng, Xi},
 booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
 pages={12556--12565},
 year={2020}
}

NeurIPS

Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness

[NeurIPS'20] Long Zhao, Ting Liu, Xi Peng, Dimitris N Metaxas.

In Proceedings of Advances in Neural Information Processing Systems, 2020. (acceptance rate 20%)

Paper

@article{zhao2020maximum,
 title={Maximum-entropy adversarial data augmentation for improved generalization and robustness},
 author={Zhao, Long and Liu, Ting and Peng, Xi and Metaxas, Dimitris},
 journal={Advances in Neural Information Processing Systems},
 volume={33},
 pages={14435--14447},
 year={2020}
}

CVPR

Knowledge as Priors: Cross-Modal Knowledge Generalization for Datasets without Superior Knowledge

[CVPR'20] Long Zhao, Xi Peng, Yuxiao Chen, Mubbasir Kapadia, and Dimitris N Metaxas.

In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2020. (acceptance rate 22%)

Paper

@inproceedings{zhao2020knowledge,
 title={Knowledge as priors: Cross-modal knowledge generalization for datasets without superior knowledge},
 author={Zhao, Long and Peng, Xi and Chen, Yuxiao and Kapadia, Mubbasir and Metaxas, Dimitris N},
 booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
 pages={6528--6537},
 year={2020}
}

IJCV

Towards Image-to-Video Translation: A Structure-Aware Approach via Multi-stage Generative Adversarial Networks

[IJCV'20, IF=13.3] Long Zhao, Xi Peng, Yu Tian, Mubbasir Kapadia, Dimitris N Metaxas.

International Journal of Computer Vision, 2020.

Paper

@article{zhao2020towards,
 title={Towards image-to-video translation: A structure-aware approach via multi-stage generative adversarial networks},
 author={Zhao, Long and Peng, Xi and Tian, Yu and Kapadia, Mubbasir and Metaxas, Dimitris N},
 journal={International Journal of Computer Vision},
 volume={128},
 number={10},
 pages={2514--2533},
 year={2020},
 publisher={Springer}
}

IJCV

CR-GAN: Learning Complete Representations for Multi-view Generation

[IJCV'20, IF=13.3] Yu Tian, Xi Peng, Long Zhao, Kang Li, Dimitris N Metaxas.

International Journal of Computer Vision, 2020. (under review)

Paper

@inproceedings{tian2018cr,
 title={CR-GAN: learning complete representations for multi-view generation},
 author={Tian, Yu and Peng, Xi and Zhao, Long and Zhang, Shaoting and Metaxas, Dimitris N},
 booktitle={Proceedings of the 27th International Joint Conference on Artificial Intelligence},
 pages={942--948},
 year={2018}
}

Automatic Health Problem Detection from Gait Videos Using Deep Neural Networks

[arXiv] Rahil Mehrizi, Xi Peng, Shaoting Zhang, Ruisong Liao, Kang Li.

arXiv, 2020.

Paper

@article{mehrizi2019automatic,
 title={Automatic health problem detection from gait videos using deep neural networks},
 author={Mehrizi, Rahil and Peng, Xi and Zhang, Shaoting and Liao, Ruisong and Li, Kang},
 journal={arXiv preprint arXiv:1906.01480},
 year={2019}
}

2019

NeurIPS

Rethinking Kernel Methods for Node Representation Learning on Graphs

[NeurIPS'19] Yu Tian*, Long Zhao*, Xi Peng, Dimitris N Metaxas.

In Proceedings of Advances in Neural Information Processing Systems, 2019. (*contributed equally) (acceptance rate 21%)

PaperPosterCode

@article{tian2019rethinking,
 title={Rethinking kernel methods for node representation learning on graphs},
 author={Tian, Yu and Zhao, Long and Peng, Xi and Metaxas, Dimitris},
 journal={Advances in neural information processing systems},
 volume={32},
 year={2019}
}

NeurIPS

Semantic-Guided Multi-Attention Localization for Zero-Shot Learning

[NeurIPS'19] Yizhe Zhu, Jianwen Xie, Zhiqiang Tang, Xi Peng, Ahmed Elgammal.

In Proceedings of Advances in Neural Information Processing Systems, 2019. (acceptance rate 21%)

Paper

@article{zhu2019semantic,
 title={Semantic-guided multi-attention localization for zero-shot learning},
 author={Zhu, Yizhe and Xie, Jianwen and Tang, Zhiqiang and Peng, Xi and Elgammal, Ahmed},
 journal={Advances in Neural Information Processing Systems},
 volume={32},
 year={2019}
}

CVPR

Semantic Graph Convolutional Networks for 3D Human Pose Regression

[CVPR'19] Long Zhao, Xi Peng, Yu Tian, Mubbasir Kapadia, Dimitris N Metaxas.

In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019. (acceptance rate 22%)

PaperPosterCode

@inproceedings{zhao2019semantic,
 title={Semantic graph convolutional networks for 3d human pose regression},
 author={Zhao, Long and Peng, Xi and Tian, Yu and Kapadia, Mubbasir and Metaxas, Dimitris N},
 booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
 pages={3425--3435},
 year={2019}
}

KDD

Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding

[KDD'19 Oral] Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia, Charu Aggarwal.

In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2019. (acceptance rate 9.2%)

Paper

@inproceedings{wu2019scalable,
 title={Scalable global alignment graph kernel using random features: From node embedding to graph embedding},
 author={Wu, Lingfei and Yen, Ian En-Hsu and Zhang, Zhen and Xu, Kun and Zhao, Liang and Peng, Xi and Xia, Yinglong and Aggarwal, Charu},
 booktitle={Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
 pages={1418--1428},
 year={2019}
}

ICCV

AdaTransform: Adaptive Data Transformation

[ICCV'19 Oral] Zhiqiang Tang, Xi Peng , Tingfeng Li, Yizhe Zhu, Dimitris N Metaxas.

In Proceedings of the IEEE International Conference on Computer Vision, 2019. (acceptance rate 4.7%)

Paper

@inproceedings{tang2019adatransform,
 title={Adatransform: Adaptive data transformation},
 author={Tang, Zhiqiang and Peng, Xi and Li, Tingfeng and Zhu, Yizhe and Metaxas, Dimitris N},
 booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
 pages={2998--3006},
 year={2019}
}

BMVC

Construct Dynamic Graphs for Hand Gesture Recognition via Spatial-Temporal Attention

[BMVC'19] Yuxiao Chen, Long Zhao, Xi Peng, Jianbo Yuan, Dimitris N. Metaxas.

In British Machine Vision Conference, 2019.

PaperCode

@inproceedings{chen2019construct,
 title={Construct Dynamic Graphs for Hand Gesture Recognition via Spatial-Temporal Attention},
 author={Chen, Yuxiao and Zhao, Long and Peng, Xi and Yuan, Jianbo and Metaxas, Dimitris N},
 booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
 year={2019}
}

TPAMI

Towards Efficient U-Nets: A Coupled and Quantized Approach

[TPAMI'19, IF=24.3] Zhiqiang Tang, Xi Peng* , Kang Li, Dimitri Metaxas.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019. (*corresponding author) (impact factor: 17.73)

PaperCode

@article{tang2019towards,
 title={Towards efficient u-nets: A coupled and quantized approach},
 author={Tang, Zhiqiang and Peng, Xi and Li, Kang and Metaxas, Dimitris N},
 journal={IEEE transactions on pattern analysis and machine intelligence},
 volume={42},
 number={8},
 pages={2038--2050},
 year={2019},
 publisher={IEEE}
}

CG

Cartoonish sketch-based face editing in videos using identity deformation transfer

[CG'19, IF=1.9] Long Zhao, Fangda Han, Xi Peng , Xun Zhang, Mubbasir Kapadia, Vladimir Pavlovic, Dimitris Metaxas.

Computers & Graphics, 2019.

Paper

@article{zhao2019cartoonish,
 title={Cartoonish sketch-based face editing in videos using identity deformation transfer},
 author={Zhao, Long and Han, Fangda and Peng, Xi and Zhang, Xun and Kapadia, Mubbasir and Pavlovic, Vladimir and Metaxas, Dimitris N},
 journal={Computers \& Graphics},
 volume={79},
 pages={58--68},
 year={2019},
 publisher={Elsevier}
}

THMS

Predicting 3-D Lower Back Joint Load in Lifting: A Deep Pose Estimation Approach

[THMS'19, IF=4.12] Rahil Mehrizi, Xi Peng , Dimitris Metaxas, Xu Xu, Shaoting Zhang, Kang Li.

IEEE Transactions on Human-Machine System, 2019.

Paper

@article{mehrizi2019predicting,
 title={Predicting 3-D lower back joint load in lifting: A deep pose estimation approach},
 author={Mehrizi, Rahil and Peng, Xi and Metaxas, Dimitris N and Xu, Xu and Zhang, Shaoting and Li, Kang},
 journal={IEEE Transactions on Human-Machine Systems},
 volume={49},
 number={1},
 pages={85--94},
 year={2019},
 publisher={IEEE}
}

JOB

A Deep Neural Network-based method for estimation of 3D lifting motions

[JOB'19, IF=2.7] Rahil Mehrizi, Xi Peng , Xu Xu, Kang Li.

Journal of Biomechanics, 2019.

Paper

@article{mehrizi2019deep,
 title={A Deep Neural Network-based method for estimation of 3D lifting motions},
 author={Mehrizi, Rahil and Peng, Xi and Xu, Xu and Zhang, Shaoting and Li, Kang},
 journal={Journal of biomechanics},
 volume={84},
 pages={87--93},
 year={2019},
 publisher={Elsevier}
}