* equal contribution, # corresponding author

[C.22] Learning to Detect Multi-class Anomalies with Just One Normal Image Prompt [pdf]
B.-B. Gao
In: Proc. the 18th European Conference on Computer Vision (ECCV 2024), Milan, Italy, Sep.-Oct. 2024, pp.xx-xx [CCF-B]

[C.21] Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation [pdf]
G. Gui*, B.-B. Gao*, J. Liu, C. Wang and Y. Wu
In: Proc. the 18th European Conference on Computer Vision (ECCV 2024), Milan, Italy, Sep.-Oct. 2024, pp.xx-xx [CCF-B]

[C.19] Learning Task-Aware Language-Image Representation for Class-Incremental Object Detection [pdf]
H. Zhang*, B.-B. Gao*, Y. Zeng, X. Tian, X. Tan#, Z. Zhang, Y. Qu, J. Liu and Y. Xie
In: Proc. the 38th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, Feb 2024, pp.7096-7104. [CCF-A]

[J.7] Cross-Modal Alternating Learning with Task-Aware Representations for Continual Learning [pdf]
W. Li*, B.-B. Gao*#, B. Xia, J. Wang, J. Liu, Y. Liu, C. Wang and F. Zheng
IEEE Transactions on Multimedia (IEEE TMM), 26:5911-5924, 2023. [CCF-B, SCI-1, IF:7.3]

[J.5] Jointly learning distribution and expectation in a unified framework for facial age and attractiveness estimation [pdf]
B.-B. Gao#
Neural Computing and Applications (NCA), 35(21):15583-15599, 2023. [CCF-C, SCI-3, IF:6.0]

[C.14] Decoupling Classifier for Boosting Few-shot Object Detection and Instance Segmentation [pdf]
B.-B. Gao#, X. Chen, Z. Huang, C. Nie, J. Liu, J. Lai, G. Jiang, X. Wang and C. Wang#
In: Proc. the 36th Conference on Neural Information Processing Systems (NeurIPS), New Orleans, USA, Dec 2022, pp.18640-18652. [CCF-A]

[J.4] APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation [pdf]
J. Chen*, B.-B. Gao*#, Z. Lu, J.-H. Xue, C. Wang and Q. Liao
IEEE Transactions on Multimedia (IEEE TMM), 25:4361-4373, 2022. [CCF-B, SCI-1, IF:7.3]

[J.3] Learning to Discover Multi-Class Attentional Regions for Multi-Label Image Recognition [pdf]
B.-B. Gao# and H.-Y. Zhou
IEEE Transactions on Image Processing (IEEE TIP), 20:5920-5932, 2021. [CCF-A, SCI-1, IF:10.6]

[C.7] Age Estimation Using Expectation of Label Distribution Learning [pdf]
B.-B. Gao, H.-Y. Zhou, J. Wu# and X. Geng
In: Proc. the 27th Int'l Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, Jul 2018, pp.712-718. [CCF-A]

[J.1] Deep Label Distribution Learning with Label Ambiguity [pdf]
B.-B. Gao, C. Xing, C.-W. Xie, J. Wu# and X. Geng
IEEE Transactions on Image Processing (IEEE TIP), 26(6):2825-2838, 2017. [CCF-A, SCI-1, IF:10.6]

* equal contribution, # corresponding author

[C.18] MatchDet: A Collaborative Framework for Image Matching and Object Detection [pdf]
J. Lai*, W. Wu*, B.-B. Gao#, J. Liu, J. Zhan, C. Nie, Y. Zeng and C. Wang#
In: Proc. the 38th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, Feb 2024, pp.2858-2865. [CCF-A]

[J.6] How to Reduce Change Detection to Semantic Segmentation [pdf]
G.-H. Wang, B.-B. Gao# and C. Wang
Pattern Recognition (PR), 2023. [CCF-B, SCI-1, IF:8.0]

[C.16] Clustered-patch Element Connection for Few-shot Learning [pdf]
J. Lai, S. Yang, J. Zhou, W. Wu, X. Chen, J. Liu, B.-B. Gao# and C. Wang#
In: Proc. the 32nd Int'l Joint Conference on Artificial Intelligence (IJCAI), Macao S.A.R, Aug 2023, pp.991-998. [CCF-A]

[C.8] A Coarse-to-Fine Instance Segmentation Network with Learning Boundary Representation [pdf]
F. Luo, B.-B. Gao#, J. Yan and X. Li#
In: Proc. the Int'l Joint Conference on Neural Networks (IJCNN), Shenzhen, China, Jul 2021. [CCF-C]

* equal contribution, # corresponding author

[C.23] Distribution-Aware Calibration for Object Detection with Noisy Bounding Boxes [pdf]
D. Zhou, J. Li, J. Li, J. Huang, Q. Nie, Y. Liu, B.-B. Gao, Q. Wang, P.-A. Heng and G. Chen
In: Proc. the Thirty Fifth British Machine Vision Conference (BMVC), Glasgow, Scotland, UK, Nov 2024, pp.--. [CCF-C]

[C.20] Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection [pdf]
C. Wang, W. Zhu, B.-B. Gao, Z. Gan, J. Zhang, Z. Gu, S. Qian, M. Chen and L. Ma#
In: Proc. the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle WA, USA, Jun 2024, pp.22883-22892. [CCF-A]

[C.17] Unsupervised Continual Anomaly Detection with Contrastively-learned Prompt
J. Liu*, K. Wu*, Q. Nie, Y. Chen, B.-B. Gao, Y. Liu, J. Wang, C. Wang and F. Zheng#
In: Proc. the 38th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, Feb 2024. [CCF-A]

[C.15] SpatialFormer: Semantic and Target Aware Attentions for Few-Shot Learning [pdf]
J. Lai, S. Yang, W. Wu, T. Wu, G. Jiang, X. Wang, J. Liu, B.-B. Gao, W. Zhang, Y. Xie and C. Wang#
In: Proc. the 37th AAAI Conference on Artificial Intelligence (AAAI), Washington DC, USA, Feb 2023, pp.8430-8437. [CCF-A]

[C.13] tSF: Transformer-Based Semantic Filter for Few-Shot Learning [pdf]
J. Lai, S. Yang, W. Liu, Y. Zeng, Z. Huang, W. Wu, J. Liu, B.-B. Gao and C. Wang#
In: Proc. the European Conference on Computer Vision (ECCV), Tel Aviv，Israel，Oct 2022, pp.1-19. [CCF-B]

[C.12] Towards continual adaptation in industrial anomaly detection [pdf]
W. Li, J. Zhan, J. Wang#, B. Xia, B.-B. Gao, J. Liu, C. Wang and F. Zheng#
In: Proc. the ACM Int'l Conference on Multimedia (ACM-MM), Lisboa, Portugal, Oct 2022, pp.2871–2880. [CCF-A]

[C.11] Rethinking the Metric in Few-shot Learning: From an Adaptive Multi-Distance Perspective [pdf]
J. Lai, S. Yang, G. Jiang, X. Wang, Y. Li, Z. Jia, X. Chen, J. Liu, B.-B. Gao, W. Zhang, Y. Xie# and C. Wang#
In: Proc. the ACM Int'l Conference on Multimedia (ACM-MM), Lisboa, Portugal, Oct 2022, pp.4021–4030. [CCF-A]

[C.10] Global Meets Local: Effective Multi-Label Image Classification via Category-Aware Weak Supervision [pdf]
J. Zhan, J. Liu, W. Tang, G. Jiang, X. Wang, B.-B. Gao, T. Zhang, W. Wu, W. Zhang, C. Wang# and Y. Xie#
In: Proc. the ACM Int'l Conference on Multimedia (ACM-MM), Lisboa Portugal, Portugal, Oct 2022，pp.6318–6326. [CCF-A]

[C.9] HDNet: a hierarchically decoupled network for crowd counting [pdf]
C. Gu, C. Wang, B.-B. Gao, J. Liu and T. Zhang#
In: Proc. the IEEE Int'l Conference on Multimedia and Expo (ICME), Taipei, Taiwan, Jul 2022. [CCF-B]

[J.2] Resource Constrained Deep Learning: Challenges and Practices (in Chinese) [pdf]
J. Wu#, B.-B. Gao, X.-S. Wei and J.-H. Luo
SCIENTIA SINICA Informatics, 48(5):501-510, 2018. [CCF-T1]

[C.6] Adaptive Feeding: Achieving Fast and Accurate Detections by Adaptively Combining Object Detectors [pdf]
H.-Y. Zhou, B.-B. Gao and J. Wu#
In: Proc. the IEEE Int'l Conference on Computer Vision (ICCV), Venice, Italy, Oct 2017, pp.3505-3513. [CCF-A]

[C.5] Sunrise or Sunset: Selective Comparison Learning for Subtle Attribute Recognition [pdf]
H.-Y. Zhou, B.-B. Gao and J. Wu#
In: Proc. the 28th British Machine Vision Conference (BMVC), London, UK, Sep 2017. [CCF-C]

[C.4] Exploit Bounding Box Annotations for Multi-label Object Recognition [pdf]
H. Yang, J. T. Zhou, Y. Zhang, B.-B. Gao, J. Wu# and J. Cai
In: Proc. the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, Jun 2017, pp.280-288. [CCF-A]

[C.3] Representing Sets of Instances for Visual Recognition [pdf]
J. Wu#, B.-B. Gao and G. Liu
In: Proc. the 30th AAAI Conference on Artificial Intelligence (AAAI), Phoenix, Arizona, USA, Feb 2016, pp.2237-2243. [CCF-A]

[W.5] Deep Label Distribution Learning for Apparent Age Estimation [pdf]
X. Yang, B.-B. Gao, C. Xing, Z.-W. Huo, X.-S Wei, Y. Zhou, J. Wu# and X. Geng#
In: Proc. the IEEE International Conference on Computer Vision (ICCVW 2015) workshop, Santiago, Chile, 2015, pp.102-108.

[W.4] Deep Spatial Pyramid Ensemble for Cultural Event Recognition [pdf]
X.-S. Wei, B.-B. Gao and J. Wu#
In: Proc. IEEE International Conference on Computer Vision (ICCVW 2015) workshop, Santiago, Chile, 2015, pp.38-44.

[W.3] Deep Spatial Pyramid: The Devil is Once Again in the Details [pdf]
B.-B. Gao, X.-S. Wei, J. Wu and W. Lin
arXiv:1504.05277v2, 2015, pp:1-9.

[W.2] A Fast and Robust TSVM for Pattern Classification [pdf]
B.-B. Gao and J.-J. Wang
arXiv:1711.05406, 2017, pp:1-14.

[W.1] On Maximum Margin Twin Support Vector Machine for Multi-Class Classification [pdf]
B.-B. Gao and J.-J. Wang
Journal of Southwest China Normal University (Natural Science Edition), 38(10):130-135, 2013.

[C.2] Coordinate Descent Fuzzy Twin Support Vector Machine for Classification [pdf]
B.-B. Gao, J.-J. Wang#, Y. Wang and C.-Y. Yang
In: Proc. the IEEE 14th Int'l Conference on Machine Learning and Applications (ICMLA), Miami, Florida, USA, Dec 2015, pp.7-12.

[C.1] L2-Loss Twin Support Vector Machine for Classification [pdf]
B.-B. Gao, J.-J. Wang# and H. Huang
In: Proc. the IEEE 5th Int'l Conference on Biomedical Engineering and Informatics (BMEI), Chongqing, China, Oct 2012, pp.1265-1269.