Jun Li

I am always looking for prospective Ph.D./Master's students and PostDocs. 

Criteria: self-motivated, hardworking, curious, background in machine learning/computer vision/math/computational physics/computational chemistry. 

News

• 03/2024, One paper was accepted by IEEE Trans. on Intelligent Transportation Systems and one paper was accepted by Visual Intelligence.

• 03/2024, One paper were accepted by IEEE TPAMI.

• 02/2024, Two papers were accepted by CVPR 2024 (Congrats to Zhiqiang (oral) and Junkai (poster)).

• 12/2023, One paper was accepted by AAAI 2024 (Congrats to Kun) and two papers were accepted by ICASSP2024 (Congrats to Yuqin).

• 07/2023, One paper was accepted by ICCV 2023 (Congrats to Renke and Guimin) and one paper was accepted by ACM MM 2023. 

• 04/2023, One paper was accepted by ICML 2023 (Congrats to Zhiqiang). 

• 02/2023, One paper was accepted by  IEEE Trans. on Neural Networks and Learning Systems. 

• 12/2022, One paper was accepted by  Neurocomputing. 

• 11/2022, Four papers were accepted by AAAI 2023 (Congrats to Jiayi (2), Zhiqiang (1) and Zheng (1)).

• 10/2022, One paper was accepted by Information Sciences and One paper was accepted by Pattern Recognition.

• 10/2022, One paper was accepted by BMVC 2022 

• 09/2022, One paper was accepted by NeurIPS 2022 and one paper was accepted by  IEEE Trans. on Neural Networks and Learning Systems (Congrats to Zhiqiang). 

• 08/2022, One paper was accepted by IEEE Trans. on Intelligent Transportation Systems (Congrats to Jiaxin).

• 07/2022, Two papers were accepted by ECCV 2022 (Congrats to Zhiqiang).

• 06/2022, One paper was accepted by ICIP 2022 (Congrats to Huang).

• 03/2022, I accepted the invitation to serve as a Reviewer of NeurIPS 2022.

• 03/2022, One paper was accepted by IEEE Trans. on Instrumentation & Measurement (Congrats to Xi Cheng).

• 03/2022, One paper (Industrial Style Transfer) was accepted by  CVPR2022 (Congrats to Jinchao and Fei Guo). 

• 02/2022, One paper was accepted by IEEE Trans. on Image Processing.

• 02/2022, One paper was accepted by Scientific Reports. 

• 02/2022, I accepted the invitation to serve as a Reviewer of  ACM MM 2022.

• 12/2021, I accepted the invitation to serve as a Reviewer of  ICML 2022.

• 12/2021, One paper was accepted by AAAI 2022 (Congrats to Yesong).

• 11/2021, I accepted the invitation to serve as a Reviewer of CVPR 2022.

• 09/2021, One paper was accepted by IEEE Trans. on Neural Networks and Learning Systems (Congrats to Bin). 

• 08/2021, One paper was accepted by IEEE Trans. on Neural Networks and Learning Systems.

• 07/2021, I accepted the invitation to serve as Senior Program Committee (SPC) member of AAAI 2022.

• 07/2021, Two papers were accepted by ICCV 2021 (Congrats to Haobo and Kun). 

• 06/2021, One paper was accepted by Pattern Recognition (Congrats to Yesong).

• 06/2021, I accepted the invitation to serve as a Reviewer of ICLR 2022.

• 05/2021, One paper was accepted by ICML 2021 (Congrats to Shuo). 

• 04/2021, I accepted the invitation to serve as a Reviewer of NeurIPS 2021.

• 03/2021, I accepted the invitation to serve as a Reviewer of ACM MM 2021.

• 03/2021, One paper was accepted by CVPR 2021 (Congrats to Xiang). 

• 01/2021, One paper was accepted by IEEE Trans. on Neural Networks and Learning Systems (Congrats to Shuhui).

• 01/2021, One paper was accepted by IEEE Trans. on Cybernetics. 

• 12/2020, I accepted the invitation to serve as a Reviewer of ICML 2021.

• 11/2020, One paper was accepted by IEEE Trans. on Neural Networks and Learning Systems.

• 10/2020, One paper was accepted by IEEE Trans. on Cybernetics (Congrats to Yesong). 

• 09/2020, One paper was accepted by NeurIPS 2020

• 08/2020, One paper was accepted by IEEE Signal Processing Letters.

• 06/2020, One paper was accepted by IEEE Trans. on Big Data.

• 01/2020, One paper was accepted by FG 2020. 

• 12/2019, I accepted the invitation to serve as Program Committee (PC) member of IJCAI2020. 

• 11/2019, Two papers were accepted by AAAI 2020. 

• 11/2019, One paper was accepted by IEEE Trans. on Knowledge & Data Engineering.

• 10/2019, I accepted the invitation to serve as Program Committee (PC) member of FG 2020.

• 09/2019, One paper was accepted by NeurIPS 2019

• 08/2019, I accepted the invitation to serve as Program Committee (PC) member of ACM MM Aisa 2019

• 07/2019, One paper was accepted by ICCV 2019. 

• 06/2019, I accepted the invitation to serve as Senior Program Committee (SPC) member of AAAI 2020. 

• 05/2019, One paper was accepted by IJCAI2019. 

• 03/2019, I accepted the invitation to serve as Program Committee (PC) member of ACM MM 2019. 

• 12/2018, I accepted the invitation to serve as Program Committee (PC) member of IJCAI2019. 

• 11/2018, One paper was accepted by IEEE Trans. on Image Processing.

• 11/2018, One paper was accepted by AAAI 2019. 

• 09/2018, One paper was accepted by Image and Vision Computing. 

• 09/2018, One paper was accepted by IEEE Trans. on Multimedia.

• 08/2018, One paper was accepted by  IEEE ICBK 2018. 

• 08/2018, I accepted the invitation to serve as Program Committee (PC) member of FG 2019.

• 07/2018, I accepted the invitation to serve as Program Committee (PC) member of IEEE MIPR 2019.

• 05/2018, I accepted the invitation to serve as Senior Program Committee (SPC) member of AAAI 2019. 

• 04/2018, One paper was accepted by IJCAI 2018.

Selected Publications (Google Scholar)

arXiv

2023

1. Haibo Chen, Lei Zhao, Jun Li and Jian Yang,  TSSAT: Two-Stage Statistics-Aware Transformation for Artistic Style Transfer, ACM MM 2023.

2. Renke Wang*, Guimin Que*, Shuo Chen, Xiang Li, Jun Li#, and Jian Yang, Creative Birds: Self-Supervised Single-View 3D Style Transfer, ICCV 2023. [arXiv2307.14127] [Code]

3. Zhiqiang Yan, Xiang Li, Kun Wang, Shuo Chen, Jun Li# and Jian Yang, Distortion and Uncertainty Aware Loss for Panoramic Depth Completion, ICML 2023. [openreview] 

4. Zhiqiang Yan, Kun Wang, Xiang Li, Zhenyu Zhang, Jun Li# and Jian Yang, DesNet: Decomposed Scale-Consistent Network for Unsupervised Depth Completion, AAAI, 2023. [arXiv2211.10994]

5. Jiayi Yuan, Haobo Jiang, Xiang Li, Jianjun Qian, Jun Li# and Jian Yang, Recurrent Structure Attention Guidance for Depth Super-Resolution, AAAI, 2023. [arXiv2301.13419]

6. Jiayi Yuan, Haobo Jiang, Xiang Li, Jianjun Qian, Jun Li# and Jian Yang, Structure Flow-Guided Network for Real Depth Super-Resolution, AAAI, 2023. [arXiv2301.13416] 

7. Zheng Li, Xiang Li, Lingfeng Yang, Borui Zhao, Renjie Song, Lei Luo, Jun Li and Jian Yang, Curriculum Temperature for Knowledge Distillation, AAAI, 2023. [arXiv2211.16231] 

2022

1. Zhiqiang Yan, Kun Wang, Xiang Li, Zhenyu Zhang, Guangyu Li#, Jun Li# and Jian Yang, Learning Complementary Correlations for Depth Super-Resolution with Incomplete Data in Real World, IEEE Trans. Neural Networks and Learning Systems (TNNLS), 2022.

2. Wei Zheng, Shuo Chen, Zhenyong Fu, Jun Li, Jian Yang, Streaming Feature Selection via Graph Diffusion, Information Sciences, 2022. [http]

3. Yesong Xu, Shuo Chen, Jun Li, Chunyan Xu, Jian Yang, Fast Subspace Clustering by Learning Projective Block Diagonal Representation, Pattern Recognition, 2022. [http]

4. Shuo Chen, Chen Gong, Jun Li, Jian Yang, Gang Niu, Masashi Sugiyama, Learning Contrastive Embedding in Low-Dimensional Space, NeurIPS 2022, [openreview]

5. Jiaxin Chen, Xiang Li, Jin Xie, Jun Li, Jianjun Qian and Jian Yang, CBi-GNN: Cross-Scale Bilateral Graph Neural Network for 3D Object Detection, IEEE Trans. on Intelligent Transportation Systems (TITS), 2022. [http]

6. Huang Tian, Xiang Li, Lingfeng Yan, Jun Li#, Jian Yang and Weidong Du, PPT:  Anomaly Detection Dataset of Printed Products with Templates, ICIP 2022. 

7. Zhiqiang Yan, Xiang Li, Kun Wang, Zhenyu Zhang, Jun Li#, and Jian Yang#, Multi-Modal Masked Pre-Training for Monocular Panoramic Depth Completion, ECCV 2022 [arXiv2203.09855], 2022.  (# indicates corresponding authors) 

8. Zhiqiang Yan, Kun Wang, Xiang Li, Zhenyu Zhang, Baobei Xu, Jun Li#, and Jian Yang#, RigNet: Repetitive Image Guided Network for Depth Completion, ECCV 2022 [arXiv2107.13802], (# indicates corresponding authors) 

9. Jinchao Yang, Fei Guo, Shuo Chen, Jun Li# and Jian Yang, Industrial Style Transfer with Large-scale Geometric Warping and Content Preservation, CVPR 2022  [arXiv:2203.12835], [project page]

10. Xi Cheng, Jun Li, Qiang Dai, Zhenyong Fu and Jian Yang, Fast and Light-Weight Network for Single Frame Structured Illumination Microscopy Super-Resolution, IEEE Trans. on Instrumentation & Measurement (TIM), 2022.  [arXiv:2111.09103]

11. Hao Chen, Yangzhun Zhou, Jun Li, Xiu-Shen Wei and Liang Xiao, Self-Supervised Multi-Category Counting Networks for Automatic Check-Out, IEEE Trans. on Image Processing (TIP), 2022 [http]

12. Yuerong Zhou, Guoshuai Zhao, Jun Li, Gan Sun, Xueming Qian, Benjamin Moody, Roger G. Mark, Li-wei H. Lehman, A contrastive learning approach for ICU false arrhythmia alarm reduction, Scientific Reports, (2022)12:4689. [http]

13. Yesong Xu, Shuo Chen, Jianjun Qian, Jun Li, Linearity-Aware Subspace Clustering, AAAI 2022 (oral) [http].

2021

1. Bin Sun, Jun Li, Ming Shao and Yun Fu, LRPRNet: Lightweight Deep Network by Low-Rank Pointwise Residual Convolution, IEEE Trans. Neural Networks and Learning Systems (TNNLS), 2021. [arXiv1910.11853] 

2. Zhiqiang Tao, Jun Li, Huazhu Fu, Yu Kong and Yun Fu, From Ensemble Clustering to Subspace Clustering: Cluster Structure Encoding, IEEE Trans. Neural Networks and Learning Systems (TNNLS), 2021. [http]

3. Kun Wang, Zhiqiang Yan, Xiang Li, Zhenyu Zhang, Baobei Xu, Jun Li# and Jian Yang#, Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark, ICCV 2021. (# indicates corresponding authors)  [arXiv2108.03830] [Code]

4. Haobo Jiang, Yaqi Shen,  Jin Xie, Jun Li, Jianjun Qian and Jian Yang, Sampling Network Guided Cross-Entropy Method for Unsupervised Point Cloud Registration, ICCV 2021.  [arXiv2109.06619]

5. Yesong Xu, Shuo Chen, Jun Li#, Lei Luo and Jian Yang#, Learnable Low-Rank Latent Dictionary for Subspace Clustering, Pattern Recognition, 2021.  (# indicates corresponding authors) [http]

6. Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, Masashi Sugiyama, Large-Margin Contrastive Learning with Distance Polarization Regularizer, ICML 2021. [http]

7. Xiang Li, Wenhai Wang, Xiaolin Hu, Jun Li, Jinhui Tang, Jian Yang, Generalized focal loss v2: Learning reliable localization quality estimation for dense object detection, CVPR 2021.  [arXiv2011.12885]

8. Shuhui Jiang, Jun Li and Yun Fu, Deep Learning for Fashion Style Generation, IEEE Trans. Neural Networks and Learning Systems (TNNLS), 2021. [http]

9. Jun Li, Zhiqiang Tao, Yue Wu, Bineng Zhong and Yun Fu, Large-Scale Subspace Clustering by Independent Distributed and Parallel Coding, IEEE Trans. on Cybernetics (TCYB), [http] 

2020

1. Yesong Xu, Shuo Chen, Jun Li#, Zongyan Han and Jian Yang#, Autoencoder-Based Latent Block-Diagonal Representation for Subspace Clustering, IEEE Trans. on Cybernetics (TCYB), [http] (# indicates corresponding authors) 

2. Xiang Li, Wenhai Wang, Lijun Wu, Shuo Chen, Xiaolin Hu, Jun Li, Jinhui Tang and Jian Yang, Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection, NeurIPS 2020, [arXiv] [code]

3. Wei Luo*, Hengmin Zhang*, Jun Li, and Xiu-Shen Wei, Learning Semantically Enhanced Feature for Fine-Grained Image Classification, IEEE Signal Processing Letters (SPL), arXiv, [code] (* indicates equal contribution)

4. Jun Li, Hongfu Liu, Zhiqiang Tao, Handong Zhao and Yun Fu, Learnable Subspace Clustering, IEEE Trans. Neural Networks and Learning Systems (TNNLS), arXiv:2004.04520, [code]

5. Dongdong Hou, Yang Cong, Gan Sun, Jiahua Dong, Jun Li, Kai Li,  Fast Multi-View Outlier Detection via Deep Encoder, IEEE Trans. on Big Data (TBD). [http]

6. Bin Sun, Jun Li, and Yun Fu, Block Mobilenet: Align Large-Pose Faces with <1MB Model Size, FG 2020. [http]

7. Jun Li, Gan Sun, Guoshuai Zhao and Li-wei Lehman, Robust Low-Rank Discovery of Data-Driven Partial Differential Equations, AAAI 2020. [http]

8. Gan Sun, Yang Cong, Qianqian Wang, Jun Li and Yun Fu, Lifelong Spectral Clustering, AAAI 2020. [http]

2019

1. Hongfu Liu*, Jun Li*, Yue Wu and Yun Fu, Clustering with Outlier Removal, IEEE Trans. on Knowledge & Data Engineering (TKDE), 2019,  accepted (* indicates equal contribution) [http]

2.  Shuo Chen, Lei Luo, Chen Gong, Jian Yang,  Jun Li and Heng Huang, Curvilinear Distance Metric Learning, NeurIPS 2019. [http]

3. Wei Luo, Xitong Yang, Xianjie Mo, Yuheng Lu, Larry Davis, Jun Li, Jian Yang and Ser-Nam Lim, Cross-X Learning for Fine-Grained Visual Categorization, ICCV, 2019.  [http] [code]

4. Zhiqiang Tao, Hongfu Liu, Jun Li, Zhaowen Wang, and Yun Fu,  Adversarial Graph Embedding for Ensemble Clustering, IJCAI, 2019. [http]

5. Bineng Zhong, Bai, Bing, Jun Li, Yulun Zhang and Yun Fu, Hierarchical Tracking by Reinforcement Learning based Searching and Coarse-to-fine Verifying, IEEE Trans. on Image Processing (TIP), 28(5):2331-2341, 2019.  [http]

6. Shuo Chen, Chen Gong, Jian Yang, Ying Tai, Le Hui and Jun Li, Data-Adaptive Metric Learning with Scale Alignment, AAAI, 2019. [http]

7. Qinqin Zhou, Bineng Zhong, Yulun Zhang, Jun Li and Yun Fu, Deep Alignment Network Based Multi-person Tracking with Occlusion and Motion Reasoning, IEEE Trans. on Multimedia (TMM), 21(5):1183-1194, 2019. [http]

2018

1. Yue Wu, Hongfu Liu, Jun Li and Yun Fu, Improving Face Representation Learning with Center Invariant Loss, Image and Vision Computing (IVC), 2018. [http] 

2. Gan Sun, Yang Cong, Jun Li and Yun Fu, Robust Lifelong Multi-task Multi-view Representation Learning, the 9th IEEE International Conference on Big Knowledge, (ICBK), 2018. [http] 

3. Wei Luo*, Jun Li*, Jian Yang, Wei Xu and Jian Zhang, Convolutional Sparse Auto-Encoder for Image Classification, IEEE Trans. Neural Networks and Learning Systems (TNNLS), 29(7): 3289-3294, 2018. [http] [code]  (* indicates equal contribution)  

4. Shuo Chen, Chen Gong, Jian Yang, Xiang Li, Yang Wei and Jun Li, Adversarial Metric Learning, IJCAI, 2018, [http] [code]

5. Jun Li, Heyou Chang, Jian Yang, Wei Luo and Yun Fu, Visual Representation and Classification by Learning Group Sparse Deep Stacking Network, IEEE Trans. on Image Processing (TIP), 27(1):464-476, 2018. [http]

6. Jun Li, Hongfu Liu and Yun Fu. Predictive Coding Machine for Compressed Sensing and Image Denoising. AAAI, 2018. [http]

2017

1. Jun Li, Tong Zhang, Wei Luo, Jian Yang, Xiaotong Yuan and Jian Zhang, Sparseness Analysis in the Pertraining of Deep Neural Networks, IEEE Trans. on Neural Networks and Learning Systems (TNNLS), 28(6) :1425-1438, 2017. [http] [code] 

2. Jun Li, Hongfu Liu, Handong Zhao and Yun Fu, Projective Low-rank Subspace Clustering via Learning Deep Encoder, IJCAI, 2017. [http] [code]

3. Jun Li, Handong Zhao, Zhiqiang Tao and Yun Fu, Large-scale Subspace Clustering by Fast Regression Coding, IJCAI, 2017. [http]

4. Jun Li, Yu Kong and Yun Fu, Sparse Subspace Clustering by Learning Approximation l_0 Codes, AAAI, 2017. [http]

5. Yu Kong, Zhengming Ding, Jun Li and Yun Fu, Deeply Learned View-Invariant Features for Cross-View Action Recognition, IEEE Trans. on Image Processing(TIP), 26(6):3028-3037, 2017. [http]

6. Yue Wu, Hongfu Liu, Jun Li and Yun Fu, Deep Face Recognition with Center Invariant Loss, the Thematic Workshops of ACM MM, 2017. [http]

2016

1. Jun Li, Yu Kong, Handong Zhao, Jian Yang and Yun Fu, Learning Fast Low-Rank Projection for Image Classification, IEEE Trans. on Image Processing(TIP), 25(10):4803-4814, 2016. [http]

2. Yue Wu, Jun Li, Yu Kong and Yun Fu, Deep Convolutional Neural Network with Independent Softmax for Large Scale Face Recognition, The first place in ACM Multimedia-Microsoft-MSR Image Recognition Challenge, ACM MM, 2016. [http]

3. Hayi Mao, Yue Wu, Jun Li and Yun Fu, Super Resolution of the Partial Pixelated Images with Deep Convolutional Neural Network, ACM MM, 2016. [http]

4. Lingzheng Dai, Jundi Ding, Jinhui Chen, Jun Li and Jian Yang, Object segmentation using low-rank representation with multiple block-diagonal priors, ICPR, 2016. [http]

2015 and before

1. Jun Li, Heyou Chang and Jian Yang, Sparse Deep Stacking Network for Image Classification, AAAI, 2015. [http]

2. Wei Luo, Jian Yang, Wei Xu, Jun Li and Jian Zhang, Higher-level Feature Combination via Multiple Kernel Learning for Image Classification,  Neurocomputing, 167:209-217, 2015. 

3. Jun Li, Heyou Chang and Jian Yang, Learning Discriminative Low-rank Representation for Image Classification, IJCNN 2014.

4. Jun Li, Jian Yang, Xiaotong Yuan and Zhaohua Hu, Continuous Attractors of Higher-order Recurrent Neural Networks with Infinite Neurons, Neurocomputing, 131: 388-396, 2014.

5. Jun Li, Wei Luo, Jian Yang and Xiaotong Yuan, Unsupervised Pretraining Encourages Moderate-Sparseness, ICML 2014---workshop: uLearnBio. [http]

6. Jun Li, Jian Yang and Weigen Wu, Stability and periodicity of discrete Hopfield neural networks with column arbitrary-magnitude-dominant weight matrix, Neurocomputing, 82:52-61, 2012.

7. Jun Li, Jian Yang and Yongfeng Diao, Continuous Attractors of Recurrent Neural Networks with Complex-valued Weights, IJCNN, 2012.

Awards

1. 2016, The first place in ACM Multimedia-Microsoft-MSR Image Recognition Challenge.

2. 2011, Outstanding Master's Thesis of Sichuan.

Services 

• SPC/PC Member: AAAI (2017-2020), IJCAI (2017, 2019), ACM MM (2019), IEEE FG (2017-2019), and IEEE ICMLA (2016-2018).

• Reviewer: IEEE TNNLS/TIP/TKDE/TIFS/TCVST/TBIOM, Neurocomputing, PRL, NLP, JVCI, SI&VP, JARS, OE, JEI, etc.

Contact

Jun Li,

School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China, 210094. 

Email: junli [AT] njust.edu.cn.