Mingming Gong


Selected Publications


Conference (* Equal Contribution)

  1. Alleviating Semantics Distortion in Unsupervised Low-Level Image-to-Image Translation via Structure Consistency Constraint. [PDF] [CODE]
    J. Guo, J. Li, H. Fu, M. Gong, K. Zhang, D. Tao.
    In CVPR, 2022.

  2. Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation. [PDF] [CODE]
    Y. Xu, S. Xie, W. Wu, K. Zhang, M. Gong*, K. Batmanghelich*.
    In CVPR, 2022.

  3. Few-Shot Font Generation by Learning Fine-Grained Local Styles. [PDF] [CODE]
    L. Tang, Y. Cai, J. Liu, Z. Hong, M. Gong, M. Fan, J. Han, J. L, E. Ding, J. Wang.
    In CVPR, 2022.

  4. CRIS: CLIP-Driven Referring Image Segmentation. [PDF] [CODE]
    Z. Wang, Y. Lu, Q. Li, X. Tao, Y. Guo, M. Gong, and T. Liu.
    In CVPR, 2022.

  5. Exploring Set Similarity for Dense Self-supervised Representation Learning. [PDF] [CODE]
    Z. Wang, Q. Li, G. Zhang, P. Wan, W. Zheng, N. Wang, M. Gong, and T. Liu.
    In CVPR, 2022.

  6. Fair Classification with Instance-dependent Label Noise. [PDF]
    S. Wu, M. Gong, B. Han, Y. Liu, T. Liu
    In CLeaR, 2022.

  7. A Relational Intervention Approach for Unsupervised Dynamics Generalization in Model-Based Reinforcement Learning. [PDF]
    J. Guo, M. Gong, D. Tao
    In ICLR, 2022.

  8. Rethinking Class-Prior Estimation for Positive-Unlabeled Learning. [PDF] [CODE]
    Y. Yao, T. Liu, B. Han, M. Gong, G. Niu, M. Sugiyama, and D. Tao
    In ICLR, 2022.

  9. Adversarial Robustness Through the Lens of Causality. [PDF] [CODE]
    Y. Zhang, M. Gong, T. Liu, G. Niu, X. Tian, B. Han, B. Schölkopf, and K. Zhang
    In ICLR, 2022.

  10. Sample Selection with Uncertainty of Losses for Learning with Noisy Labels. [PDF] [CODE]
    X. Xia, T. Liu, B. Han, M. Gong, J. Yu, G. Niu, and M. Sugiyama
    In ICLR, 2022.

  11. Domain Adaptation with Invariant Representation Learning: What Transformations to Learn?. [PDF] [CODE]
    P. Stojanov, Z. Li, M. Gong, R. Cai, J.G. Carbonell, and K. Zhang
    In NeurIPS, 2021.

  12. Instance-dependent Label-noise Learning under a Structural Causal Model. [PDF] [CODE]
    Y. Yao, T. Liu, M. Gong, B. Han, G. Niu, and K. Zhang.
    In NeurIPS, 2021.

  13. Unaligned Image-to-Image Translation by Learning to Reweight. [PDF] [CODE]
    S. Xie, M. Gong, Y. Xu, and K. Zhang
    In ICCV, 2021.

  14. Not All Operations Contribute Equally: Hierarchical Operation-adaptive Predictor for Neural Architecture Search. [PDF]
    Z. Chen, Y. Zhan, B. Yu, M. Gong*, and B. Du*
    In ICCV, 2021.

  15. Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels [PDF] [CODE]
    S. Wu*, X. Xia*, T. Liu, B. Han, M. Gong, N. Wang, H. Liu, and G. Niu
    In ICML, 2021.

  16. Learning with Group Noise. [PDF][CODE]
    Q. Wang, J. Yao, C. Gong, T. Liu, M. Gong, H. Yang, and B. Han.
    In AAAI, 2021.

  17. Domain Adaptation As a Problem of Inference on Graphical Models. [PDF][CODE]
    K. Zhang*, M. Gong*, P. Stojanov, B. Huang, Qingsong Liu, and C. Glymour.
    In NeurIPS, 2020.

  18. Domain Generalization via Entropy Regularization. [PDF][CODE]
    S. Zhao, M. Gong, T. Liu, H. Fu, and D. Tao.
    In NeurIPS, 2020.

  19. Parts-dependent Label Noise: Towards Instance-dependent Label Noise. [PDF][CODE]
    X. Xia, T. Liu, B. Han, N. Wang, M. Gong, H. Liu, G. Niu, D. Tao, and M. Sugiyama.
    In NeurIPS, 2020. (Spotlight)

  20. Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning. [PDF][CODE]
    Y. Yao, T. Liu, B. Han, M. Gong, J. Deng, G. Niu, and M. Sugiyama.
    In NeurIPS, 2020.

  21. Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity Learning. [PDF][CODE]
    F. Fu*, S. Li*, R. Jia, M. Gong, B. Zhao, and D. Tao.
    In NeurIPS, 2020.

  22. Short-Term and Long-Term Context Aggregation Network for Video Inpainting. [PDF]
    A. Li, S. Zhao, X. Ma, M. Gong, J. Qi, R. Zhang, D. Tao, and R. Kotagiri
    In ECCV, 2020. (Spotlight)

  23. Sub-center ArcFace: Boosting Face Recognition by Large-scale Noisy Web Faces. [PDF][CODE]
    J. Deng, J. Guo, T. Liu, M. Gong, and S Zafeiriou.
    In ECCV, 2020.

  24. Label-Noise Robust Domain Adaptation. [PDF]
    X. Yu, T. Liu, M. Gong, K. Zhang, K. Batmanghelich, and D. Tao.
    In ICML, 2020.

  25. LTF: A Label Transformation Framework for Correcting Target Shift. [PDF][CODE]
    J. Guo, M. Gong, T. Liu, K. Zhang, and D. Tao.
    In ICML, 2020.

  26. Compressed Self-Attention for Deep Metric Learning with Low-Rank Approximation. [PDF]
    Z. Chen, M. Gong*, L. Ge, B. Du*.
    In IJCAI, 2020.

  27. Causal Discovery from Non-Identical Variable Sets. [PDF]
    B. Huang, K. Zhang, M. Gong, and C. Glymour.
    In AAAI, 2020.

  28. Generative-Discriminative Complementary Learning. [PDF][CODE]
    Y. Xu*, M. Gong*, J. Chen, T. Liu, K. Zhang, and K. Batmanghelich.
    In AAAI, 2020.

  29. Compressed Self-Attention for Deep Metric Learning. [PDF]
    Z. Chen, M. Gong, Y. Xu, C. Wang, K. Zhang, B. Du.
    In AAAI, 2020.

  30. Twin Auxiliary Classifiers GAN. [PDF][CODE]
    M. Gong*, Y. Xu*, C. Li, K. Zhang, and K. Batmanghelich.
    In NeurIPS, 2019. (Spotlight, acceptance rate 2.4%)

  31. Likelihood-Free Overcomplete ICA and Applications in Causal Discovery. [PDF][CODE]
    C. Ding, M. Gong, K. Zhang, and D. Tao.
    In NeurIPS, 2019. (Spotlight, acceptance rate 2.4%)

  32. Specific and Shared Causal Relation Modeling and Mechanism-based Clustering. [PDF]
    B. Huang, K. Zhang, P. Xie, M. Gong, E. P. Xing, and C. Glymour.
    In NeurIPS, 2019.

  33. Discovery and Forecasting in Nonstationary Environments with State-Space Models. [PDF][SUPP][CODE]
    B. Huang, K. Zhang, M. Gong, and C. Glymour.
    In ICML, 2019.

  34. Geometry-Consistent Adversarial Networks for Unsupervised Domain Mapping. [PDF][CODE]
    H. Fu*, M. Gong*, C. Wang, K. Batmanghelich, K. Zhang, and D. Tao.
    In CVPR, 2019. (best paper finalist, top 1%)

  35. Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation. [PDF][CODE]
    S. Zhao, H. Fu, M. Gong, and D. Tao.
    In CVPR, 2019.

  36. Low-Dimensional Density Ratio Estimation for Covariate Shift Correction. [PDF]
    P. Stojanov, M. Gong, J. G. Carbonell, and K. Zhang.
    In AISTATS, 2019.

  37. Data-Driven Approach to Multiple-Source Domain Adaptation. [PDF]
    P. Stojanov, M. Gong, J. G. Carbonell, and K. Zhang.
    In AISTATS, 2019.

  38. Modeling Dynamic Missingness of Implicit Feedback for Recommendation. [PDF]
    M. Wang, M. Gong, X. Zheng, and K. Zhang.
    In NeurIPS, 2018.

  39. Causal Discovery with Linear Non-Gaussian Models under Measurement Error: Structural Identifiability Results. [PDF]
    K. Zhang, M. Gong, J. Ramsey, K. Batmanghelich, P. Spirtes, and C. Glymour​.
    In UAI, 2018. (Oral, acceptance rate 8.9%)

  40. Generative-Discriminative Approach from a Bag of Image Patches to a Vector. [PDF]
    S. Singla, M. Gong, S. Ravanbakhsh, B. Poczos, and K. Batmanghelich.
    In MICCAI, 2018.

  41. Learning with Biased Complementary Labels. [PDF]
    X. Yu, T. Liu, M. Gong, and D. Tao.
    In ECCV, 2018. (Oral, acceptance rate 2.4%)

  42. Correcting the Triplet Selection Bias for Triplet Loss. [PDF][CODE]
    B. Yu, T. Liu, M. Gong, C. Ding, and D. Tao.
    In ECCV, 2018.

  43. Deep Domain Generalization via Conditional Invariant Adversarial Networks. [PDF][CODE]
    Y. Li, X. Tian, M. Gong, Y. Liu, T. Liu, K. Zhang, and D. Tao.
    In ECCV, 2018.

  44. Deep Ordinal Regression Network for Monocular Depth Estimation. [PDF][CODE]
    H. Fu, M. Gong, C. Wang, K. Batmanghelich, and D. Tao.
    In CVPR, 2018.
    This algorithm won the 1st prize in single image depth prediction competition, Robust Vision Challenge 2018.

  45. An Efficient and Provable Approach for Mixture Proportion Estimation Using Linear Independence Assumption. [PDF][CODE]
    X. Yu, T. Liu, M. Gong, K. Batmanghelich, and D. Tao.
    In CVPR, 2018.

  46. Domain Generalization via Conditional Invariant Representations. [PDF][CODE]
    Y. Li, M. Gong, X. Tian, T. Liu, and D. Tao.
    In AAAI, 2018 (Oral, acceptance rate 11.0%)

  47. Causal Discovery from Temporally Aggregated Time Series. [PDF]
    M. Gong, K. Zhang, B. Schölkopf, C. Glymour, and D. Tao.
    In UAI, 2017.

  48. A Coarse-Fine Network for Keypoint Localization. [PDF]
    S. Huang, M. Gong, and D. Tao.
    In ICCV, 2017. (Spotlight, acceptance rate 2.6%)

  49. Domain Adaptation with Conditional Transferable Components. [PDF][CODE]
    M. Gong, K. Zhang, T. Liu, D. Tao, C. Glymour, and B. Schölkopf.
    In ICML, 2016.

  50. Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components. [PDF][CODE]
    P. Geiger, K. Zhang, M. Gong, B. Schölkopf, and D. Janzing.
    In ICML, 2015.

  51. Discovering Temporal Causal Relations from Subsampled Data. [PDF][CODE]
    M. Gong*, K. Zhang*, B. Schölkopf, D. Tao, and P. Geiger.
    In ICML, 2015.

  52. Multi-Source Domain Adaptation: A Causal View. [PDF][CODE]
    K. Zhang, M. Gong, and B. Schölkopf.
    In AAAI, 2015.


Journal

  1. Learning Multi-level Weight-centric Features for Few-shot Learning. [PDF]
    M. Liang, S. Huang, S. Pan, M. Gong, W. Liu.
    Pattern Recognition, to appear (2022).

  2. Deep Learning is Singular, and That's Good. [PDF]
    S. Wei, D. Murfet, M. Gong, H. Li, J. Gell-Redman, T. Quella.
    IEEE T-NNLS,, to appear (2022).

  3. Uncertainty-aware clustering for unsupervised domain adaptive object re-identification. [PDF][CODE]
    P. Wang, C. Ding, W. Tan, M. Gong, K. Jia, D. Tao.
    IEEE T-MM, to appear (2022).

  4. A Unified B-Spline Framework for Scale-Invariant Keypoint Detection. [PDF][CODE]
    Q. Zheng, M. Gong, X. You, and D. Tao.
    IJCV, (2022).

  5. 3D-FUTURE: 3D Furniture shape with TextURE. [PDF]
    H. Fu, R. Jia, L. Gao, M. Gong, B. Zhao, S. Maybank, and D. Tao.
    IJCV, 129(12), 3313-3337 (2021).

  6. Adaptive Context-Aware Multi-Modal Network for Depth Completion. [PDF]
    S. Zhao, M. Gong, H. Fu, D. Tao
    IEEE T-IP, 30, 5264-5276 (2021).

  7. HRSiam: High-Resolution Siamese Network, Towards Space-Borne Satellite Video Tracking. [PDF]
    J. Shao, B. Du, C. Wu, M. Gong, T. Liu
    IEEE T-IP, 30, 3056-3068 (2021).

  8. Unpaired Data Empowers Association Tests. [PDF]
    M. Gong, P. Liu, F. C. Sciurba, P. Stojanov, D. Tao, G. C. Tseng, K. Zhang, K. Batmanghelich
    Bioinformatics, 37, 785-792 (2021).

  9. LogDet Metric-Based Domain Adaptation. [PDF]
    Y. Liu, B. Du, W. Tu, M. Gong, Y. Guo, and D. Tao.
    IEEE T-NNLS, 2129-2142 (2020).

  10. Learning the Implicit Strain Reconstruction in Ultrasound Elastography using Privileged Information. [PDF]
    Z. Gao, S. Wu, Z. Liu, J. Luo, H. Zhang, M. Gong, and S. Li.
    Medical Image Analysis, 58, (2019).

  11. Receptive Field Size Versus Model Depth for Single Image Super-Resolution. [PDF]
    R. Wang, M. Gong, D. Tao.
    IEEE T-IP, 29: 1669-1682 (2019).

  12. MoE-SPNet: A mixture-of-experts scene parsing network. [PDF]
    F. Hu, M. Gong, C. Wang, and D. Tao.
    Pattern Recognition, 84: 226-236 (2018).

  13. Large Cone Non-negative Matrix Factorization. [PDF]
    T. Liu, M. Gong, and D. Tao.
    IEEE T-NNLS, 28(9): 2129-2142 (2017).

  14. DERF: Distinctive Efficient Robust Features From the Biological Modeling of the P Ganglion Cells. [PDF]
    D. Weng, Y. Wang, M. Gong, D. Tao, H. Wei, and D. Huang.
    IEEE T-IP, 24(8): 2287-2302 (2015).