publications

publications by categories in reversed chronological order. generated by jekyll-scholar.

2024

  1. AAAI
    M3SOT: Multi-frame, Multi-field, Multi-space 3D Single Object Tracking
    Jiaming Liu, Yue Wu, Maoguo Gong, Qiguang Miao, Wenping Ma, and Can Qin
    In Proceedings of the AAAI Conference on Artificial Intelligence, 2024

2023

  1. arXiv
    HIVE: Harnessing Human Feedback for Instructional Visual Editing
    Shu Zhang, Xinyi Yang, Yihao Feng, Can Qin, Chia-Chih Chen, Ning Yu, Zeyuan Chen, Huan Wang, Silvio Savarese, Stefano Ermon, Caiming Xiong, and Ran Xu
    arXiv preprint arXiv:2303.09618, 2023
  2. arXiv
    Why is the state of neural network pruning so confusing? on the fairness, comparison setup, and trainability in network pruning
    Huan Wang, Can Qin, Yue Bai, and Yun Fu
    arXiv:2301.05219, 2023
  3. NeurIPS
    UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild
    Can Qin, Shu Zhang, Ning Yu, Yihao Feng, Xinyi Yang, Yingbo Zhou, Huan Wang, Juan Carlos Niebles, Caiming Xiong, Silvio Savarese, Stefano Ermon, Yun Fu, and Ran Xu
    Advances in Neural Information Processing Systems, 2023
  4. ICDM
    Rethinking Adam: A twofold exponential moving average approach
    Yizhou Wang, Yue Kang, Can Qin, Huan Wang, Yi Xu, Yulun Zhang, and Yun Fu
    IEEE International Conference on Data Mining, 2023
  5. ICCV
    GlueGen: Plug and Play Multi-modal Encoders for X-to-image Generation
    Can Qin, Ning Yu, Chen Xing, Shu Zhang, Zeyuan Chen, Stefano Ermon, Yun Fu, Caiming Xiong, and Ran Xu
    International Conference on Computer Vision, 2023
  6. TIP
    Balancing biases and preserving privacy on balanced faces in the wild
    Joseph P Robinson, Can Qin, Yann Henon, Samson Timoner, and Yun Fu
    IEEE Transactions on Image Processing, 2023
  7. TPAMI
    Global Aligned Structured Sparsity Learning for Efficient Image Super-Resolution
    Huan Wang, Yulun Zhang, Can Qin, Luc Van Gool, and Yun Fu
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
  8. CVPR
    Mask-free OVIS: Open-Vocabulary Instance Segmentation without Manual Mask Annotations
    Vibashan VS, Ning Yu, Chen Xing, Can Qin, Mingfei Gao, Juan Carlos Niebles, Vishal M Patel, and Ran Xu
    In IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
  9. ICLR Oral
    Image as Set of Points
    Xu Ma, Yuqian Zhou, Huan Wang, Can Qin, Bin Sun, Chang Liu, and Yun Fu
    In The Eleventh International Conference on Learning Representations, 2023

2022

  1. arXiv
    A Close Look at Spatial Modeling: From Attention to Convolution
    Xu Ma, Huan Wang, Can Qin, Kunpeng Li, Xingchen Zhao, Jie Fu, and Yun Fu
    arXiv preprint arXiv:2212.12552, 2022
  2. ICDM
    Making Reconstruction-based Method Great Again for Video Anomaly Detection
    Yizhou Wang, Can Qin, Yue Bai, Yi Xu, Xu Ma, and Yun Fu
    In 2022 IEEE International Conference on Data Mining, 2022
  3. TIP
    Semi-Supervised Domain Adaptive Structure Learning
    Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, and Yun Fu
    IEEE Transactions on Image Processing, 2022
  4. KDD
    External Knowledge Infusion for Tabular Pre-training Models with Dual-adapters
    Can Qin, Sungchul Kim, Handong Zhao, Tong Yu, Ryan A Rossi, and Yun Fu
    In ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022
  5. ICLR
    Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework
    Xu Ma, Can Qin, Haoxuan You, Haoxi Ran, and Yun Fu
    In International Conference on Learning Representations, 2022
  6. ICLR
    Learning Efficient Image Super-Resolution Networks via Structure-Regularized Pruning
    Yulun Zhang*, Huan Wang*, Can Qin, and Yun Fu
    In International Conference on Learning Representations, 2022
  7. Nature Comm
    Self-directed online machine learning for topology optimization
    Changyu Deng, Yizhou Wang, Can Qin, Yun Fu, and Wei Lu
    Nature communications, 2022

2021

  1. FG
    The 5th recognizing families in the wild data challenge: Predicting kinship from faces
    Joseph P Robinson, Can Qin, Ming Shao, Matthew A Turk, Rama Chellappa, and Yun Fu
    In IEEE International Conference on Automatic Face and Gesture Recognition, 2021
  2. NeurIPS
    Slow learning and fast inference: Efficient graph similarity computation via knowledge distillation
    Can Qin, Handong Zhao, Lichen Wang, Huan Wang, Yulun Zhang, and Yun Fu
    Advances in Neural Information Processing Systems, 2021
  3. NeurIPS Spotlight
    Aligned structured sparsity learning for efficient image super-resolution
    Yulun Zhang*, Huan Wang*, Can Qin, and Yun Fu
    Advances in Neural Information Processing Systems, 2021
  4. ICCV
    Context reasoning attention network for image super-resolution
    Yulun Zhang, Donglai Wei, Can Qin, Huan Wang, Hanspeter Pfister, and Yun Fu
    In Proceedings of the IEEE/CVF International Conference on Computer Vision, 2021
  5. SDM
    Contradictory structure learning for semi-supervised domain adaptation
    Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, and Yun Fu
    In SIAM International Conference on Data Mining, 2021
  6. ICLR
    Neural pruning via growing regularization
    Huan Wang, Can Qin, Yulun Zhang, and Yun Fu
    International Conference on Learning Representations, 2021

2020

  1. CVPRW
    Face recognition: too bias, or not too bias?
    Joseph P Robinson, Gennady Livitz, Yann Henon, Can Qin, Yun Fu, and Samson Timoner
    In IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2020
  2. ECCV
    Generative view-correlation adaptation for semi-supervised multi-view learning
    Yunyu Liu, Lichen Wang, Yue Bai, Can Qin, Zhengming Ding, and Yun Fu
    In European Conference on Computer Vision, 2020
  3. AAAI
    Dual relation semi-supervised multi-label learning
    Lichen Wang, Yunyu Liu, Can Qin, Gan Sun, and Yun Fu
    In Proceedings of the AAAI Conference on Artificial Intelligence, 2020
  4. Remote Sensing
    Semi-supervised hyperspectral image classification via spatial-regulated self-training
    Yue Wu, Guifeng Mu, Can Qin, Qiguang Miao, Wenping Ma, and Xiangrong Zhang
    Remote Sensing, 2020

2019

  1. NeurIPS
    Pointdan: A multi-scale 3d domain adaption network for point cloud representation
    Can Qin*, Haoxuan You*, Lichen Wang, C-C Jay Kuo, and Yun Fu
    Advances in Neural Information Processing Systems, 2019
  2. ICCVW
    Generatively inferential co-training for unsupervised domain adaptation
    Can Qin, Lichen Wang, Yulun Zhang, and Yun Fu
    In IEEE/CVF International Conference on Computer Vision Workshops, 2019