林绍辉

林绍辉博士，华东师范大学计算机学院青年研究员，紫江青年学者，2021年扬帆计划获得者。于2019年博士毕业于厦门大学信息学院，师从纪荣嵘教授。同年，进入新加坡国立大学计算机学院担任博士后研究员。目前主要研究方向有计算机视觉、机器学习、图像视频理解、低层视觉，特别是深度模型压缩与加速。在国际顶级期刊和会议，TPAMI、TNNLS、Neurocomputing、CVPR、ECCV、AAAI、IJCAI等，以第一作者或通信作者身份发表近15篇论文。担任IJCAI 2020 SPC以及国际顶级期刊和会议（如：TPAMI、TIP、IJCV、TNNLS、TMM、PR、CVPR、NeurIPS、ICML等）审稿人。个人主页：https://sites.google.com/site/shaohuilin007

课题组长期招收博士生，硕士生，欢迎感兴趣的同学咨询，邮件请发送到shlin@cs.ecnu.edu.cn

副主编/领域主席：担任国际人工智能顶级会议IJCAI资深程序委员会委员（SPC）、CVPR 2024 AC、PRCV 2023/2024 AC

期刊审稿人：IEEE Transactions on Pattern analysis and Machine intelligence(TPAMI), International Journal of Computer Vision (IJCV), IEEE Transactions on Neural Networks and Learning System (TNNLS), IEEE Transactions on Image Processing, IEEE Transactions on Multimedia (TMM), Pattern Recognition (PR), Neural Networks等

会议审稿人：CVPR 2020, NeurIPS 2020, AAAI 2021, IJCAI 2021, ICML 2021, ICCV 2021等

计算机视觉、机器学习、模型压缩与加速、低层视觉

部分成果列表如下 (*通信作者，#共同一作)：

2024年：

1. Yunchen Li, Zhou Yu, Gaoqi He, Yunhang Shen, Ke Li, Xing Sun, Shaohui Lin*. SPD-DDPM: Denoising Diffusion Probabilistic Models in the Symmetric Positive Definite Space. In AAAI 2024. (CCF A)

2. Runqi Wang, Huixin Sun, Linlin Yang, Shaohui Lin, Chuanjian Liu, Yan Gao, Yao Hu, Baochang Zhang. AQ-DETR: Low-Bit Quantized Detection Transformer with Auxiliary Queries. In AAAI 2024. (CCF A)

3.  Lianggangxu Chen, Youqi Song, Shaohui Lin, Changbo Wang, Gaoqi He. Kumaraswamy Wavelet for Heterophilic Scene Graph Generation. In AAAI, 2024. (CCF A)

4. Jianghang Lin, Yunhang Shen, Bingquan Wang, Shaohui Lin, Ke Li, Liujuan Cao. Weakly Supervised Open-Vocabulary Object Detection. In AAAI, 2024. (CCF A)

5. Wenxuan Huang, Yunhang Shen, Jiao Xie, Baochang Zhang, Gaoqi He, Ke Li, Xing Sun, Shaohui Lin*. A General and Efficient Training for Transformer via Token Expansion. In CVPR, 2024. (CCF A)

6. Yunhang Shen, Chaoyou Fu, Peixian Chen, Mengdan Zhang, Ke Li, Xing Sun, Yunsheng Wu, Shaohui Lin*, Rongrong Ji. Aligning and Prompting Everything All at Once for Universal Visual Perception. In CVPR, 2024. (CCF A)

7. Lianggangxu Chen, Xuejiao Wang, Jiale Lu, Shaohui Lin, Changbo Wang, Gaoqi He. CLIP-Driven Open-Vocabulary 3D Scene Graph Generation via Cross-Modality Contrastive Learning. In CVPR, 2024. (CCF A)

8. Zikai Zhou, Yunhang Shen, Shitong Shao, Linrui Gong, Shaohui Lin*. Rethinking Centered Kernel Alignment in Knowledge Distillation. In IJCAI, 2024. (CCF A)

9. 王楠，林绍辉*，齐福霖等. 基于自监督学习的医学影像异常检测. 计算机辅助设计与图形学学报, 2024. (CCF A中文)

2023年：

1. Linrui Gong, Shaohui Lin*, Baochang Zhang, Yunhang Shen, Ke Li, Ruizhi Qiao, Bo Ren, Muqing Li, Zhou Yu, Lizhuang Ma. Adaptive Hierarchy-Branch Fusion for Online Knowledge Distillation. In AAAI 2023. （CCF A）

2. Yiqing Cai, Lianggangxu Chen, Haoyue Guan, Shaohui Lin*, Changhong Lu, Changbo Wang, Gaoqi He*. Explicit Invariant Feature Induced Cross-Domain Crowd Counting. In AAAI 2023. （CCF A）

3. Runqi Wang, Xiaoyue Duan, Guoliang Kang, Jianzhuang Liu, Shaohui Lin, Songcen Xu, Jinhu Lu, Baochang Zhang. AttriCLIP: A Non-Incremental Learner for Incremental Knowledge Learning. In CVPR, 2023. （CCF A）

4. Nan Wang, Shaohui Lin*, Xiaoxiao Li, Ke Li, Yunhang Shen, Yue Gao, Lizhuang Ma*. MISSU: 3D Medical Image Segmentation via Self-distilling TransUNet[J]. IEEE Transactions on Medical Imaging, 2023. (JCR 1区，CCF B，医学影像顶级期刊)

5. Jiao Xie, Shaohui Lin*, Yichen Zhang, Linkai Luo*. Compressing convolutional neural networks with cheap convolutions and online distillation[J]. Displays, 2023. （中科院SCI 2区）

6. Nan Wang, Chengwei Chen, Shaohui Lin*, Lizhuang Ma*. Latent Feature Regularization based Adversarial Network for Brain Tumor Anomaly Detection. In ICME, 2023. (CCF B)

7. Jiale Lu, Lianggangxu Chen, Youqi Song, Shaohui Lin*, Changbo Wang, Gaoqi He*. Prior Knowledge-driven Dynamic Scene Graph Generation with Causal Inference. In ACM MM, 2023. (CCF A)

8. Jiao Xie, Linrui Gong, Shitong Shao, Shaohui Lin, Linkai Luo. Hybrid knowledge distillation from intermediate layers for efficient Single Image Super-Resolution [J]. In Neurocomputing, 2023. (CCF C, 中科院SCI 2区)

9. Chong Huang, Shaohui Lin*, Yan Zhang, Ke Li, Baochang Zhang. Data-Free Low-Bit Quantization via Dynamic Multi-teacher Knowledge Distillation. In PRCV, 2023. (CCF C)

10. Xiangchuang Chen, Yunhang Shen, Xuan Luo, Yan Zhang, Ke Li, Shaohui Lin*. Classifier Decoupled Training for Black-Box Unsupervised Domain Adaptation. In PRCV, 2023. (CCF C)

11. Shaohui Lin, Bo Ji, Rongrong Ji, Angela Yao. A closer look at branch classifiers of multi-exit architectures[J]. In CVIU, 2023. (CCF B)

12. Jiale Lu, Lianggangxu Chen, Haoyue Guan, Shaohui Lin, Chunhua Gu, Changbo Wang, Gaoqi He. Improving rare relation inferring for scene graph generation using bipartite graph network[J]. In CVIU, 2023. (CCF B)

2022年：

1. Chengwei Chen, Yuan Xie, Shaohui Lin, et al. Comprehensive Regularization in a Bi-directional Predictive Network for Video Anomaly Detection. AAAI, 2022. (CCF A)

2. Mengtian Li, Yuan Xie, Yunhang Shen, Bo Ke, Ruizhi Qiao, Bo Ren, Shaohui Lin*, Lizhuang Ma*. HybridCR: Weakly-Supervised 3D Point Cloud Semantic Segmentation via Hybrid Contrastive Regularization. In CVPR, 2022. (CCF A)

3. Haiyan Wu, Yuting Gao, Yinqi Zhang, Shaohui Lin*, Yuan Xie*, Xing Sun, Ke Li. Self-Supervised Models are Good Teaching Assistants for Vision Transformers. In ICML, 2022. (CCF A)

4. Yuting Gao, Jia-Xin Zhuang, Shaohui Lin, Hao Cheng, Xing Sun, Ke Li, Chunhua Shen. DisCo: Remedying Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning. In ECCV, 2022. (CCF B, Oral)

2021年：

1. Xudong Tian, Zhizhong Zhang*, Shaohui Lin, Yanyun Qu, Yuan Xie*, Lizhuang Ma. Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification. CVPR, 2021. (CCF A Oral)

2. Haiyan Wu, Yanyun Qu, Shaohui Lin*, Jian Zhou, Ruizhi Qiao, Zhizhong Zhang, Yuan Xie*, Lizhuang Ma. Contrastive Learning for Compact Single Image Dehazing. CVPR, 2021. (CCF A)

3. Yuchao Li#, Shaohui Lin#, Jianzhuang Liu, et al. Towards Compact CNNs via Collaborative Compression. CVPR, 2021. (CCF A)

4. Yanbo Wang, Shaohui Lin*, Yanyun Qu, et al. Towards Compact Single Image Super-Resolution via Contrastive Self-distillation. IJCAI, 2021. (CCF A)

5. Chengwei Chen, Yuan Xie, Shaohui Lin*, et al. Novelty Detection via Contrastive Learning with Negative Data Augmentation. IJCAI, 2021. (CCF A)

6. Xuncheng Liu, Xudong Tian, Shaohui Lin, et al. Learn from Concepts: Towards the Purified Memory for Few-shot Learning. IJCAI, 2021. (CCF A)    

2020年：

1. Shaohui Lin, Rongrong Ji*, Yuchao Li, Cheng Deng, Xuelong Li. Toward Compact ConvNet via Structure-sparsity Regularized Filter Pruning. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020, 31(2): 574-588 (SCI, CCF B, JCR 1)

2. Yuchao Li, Rongrong Ji*, Shaohui Lin, Baochang Zhang, Chenqian Yan, Yongjian Wu, Feiyue Huang, Ling Shao.Interpretable Neural Networks Decoupling. European Conference on Computer Vision (ECCV), 2020 (CCF B)

3.Huixia Li, Chenqian Yan, Shaohui Lin, Xiawu Zheng, Baochang Zhang, Fan Yang, Rongrong Ji*. PAMS: Quantized Super-Resolution via Parameterized Max Scale. European Conference on Computer Vision (ECCV), 2020 (CCF B)

4. Moritz Wolter, Shaohui Lin,Angela Yao. Neural Network Compression via Learnable Wavelet Transforms. International Conference on Artificial Neural Networks (ICANN), 2020 (CCF C)

2019年：

1. Shaohui Lin, Rongrong Ji, Chao Chen, Dacheng Tao, Jiebo Luo. Holistic CNN Compression via Low-rank Decomposition with Knowledge Transfer. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019, 41(12): 2889-2905 (SCI, CCF A, JCR 1).

2. Shaohui Lin, Rongrong Ji, Chenqian Yan, Baochang Zhang, Liujuan Cao, Qixiang Ye, Feiyue Huang, David Doermann. Towards Optimal Structured CNN Pruning via Generative Adversarial Learning. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 (CCF A).

3. Yuchao Li#, Shaohui Lin#, Baochang Zhang, Jianzhuang Liu, David Doermann, Yongjian Wu, Feiyue Huang, Rongrong Ji. Exploiting Kernel Sparsity and Entropy for Interpretable CNN Compression. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 (CCF A). 

4. Zongyue Wang, Shaohui Lin*, Jiao Xie, Yangbin Lin. Pruning Blocks for CNN Compression and Acceleration via Online Ensemble Distillation. IEEE Access, 2019. (JCR2)

2018年：

1. Shaohui Lin, Rongrong Ji, Yuchao Li, Yongjian Wu, Feiyue Huang, Baochang Zhang. Accelerating Convolutional Networks via Global & Dynamic Filter Pruning. International Joint Conference on Artificial Intelligence (IJCAI), 2018: 2425- 2432. (CCF A).

2. Rongrong Ji, Shaohui Lin*, Fei Chao, Yongjian Wu, Feiyue Huang. 深度神经网络压缩与加速综述. 计算机研究与发展, 2018, 55(9): 1871-1888. (CCF A 国内期刊).

2017年：

1. Shaohui Lin, Rongrong Ji, Chao Chen, Feiyue Huang. ESPACE: Accelerating Convolutional Neural Networks via Eliminating Spatial & Channel Redundancy. AAAI Conference on Artificial Intelligence (AAAI), 2017: 1424-1430 (CCF A, Oral).

2016年：

1. Shaohui Lin, Rongrong Ji, Xiaowei Guo, Xuelong Li. Towards Convolutional Neural Networks Compression via Global Error Reconstruction. International Joint Conference on Artificial Intelligence (IJCAI), 2016: 1753-1759 (CCF A).

2. Shaohui Lin, Ling Cai, Xianming Lin, Rongrong Ji. Masked Face Detection via A Modified LeNet. Neurocomputing, 2016, 218: 197-202. (SCI, CCF C, JCR 2).

2019年福建省优秀博士学位论文奖

2020年中国人工智能学会优秀博士学位论文提名奖