0%
2024
- ADA-GAD: Anomaly-Denoised Autoencoders for Graph Anomaly Detection
Junwei He, Qianqian Xu, Yangbangyan Jiang, Zitai Wang and Qingming Huang.
AAAI 2024 (CCF-A) [code]
- Regularized Contrastive Partial Multi-view Outlier Detection
Junwei He, Qianqian Xu, Yangbangyan Jiang, Zitai Wang, Yuchen Sun and Qingming Huang.
ACM MM 2024 (CCF-A, Full paper) [pdf] [code]
- HGOE: Hybrid External and Internal Graph Outlier Exposure for Graph Out-of-Distribution Detection
Yijia Wang, Qianqian Xu, Yangbangyan Jiang, Siran Dai and Qingming Huang.
ACM MM 2024 (CCF-A, Full paper) [pdf] [code]
2023
- Positive-Unlabeled Learning with Label Distribution Alignment
Yangbangyan Jiang, Qianqian Xu, Yunrui Zhao, Zhiyong Yang, Peisong Wen, Xiaochun Cao and Qingming Huang
IEEE TPAMI 2023 (CCF-A, Regular paper) [code]
- PSNEA: Pseudo-Siamese Network for Entity Alignment between Multi-modal Knowledge Graphs
Wenxin Ni, Qianqian Xu, Yangbangyan Jiang, Zongsheng Cao, Xiaochun Cao, Qingming Huang
ACM MM 2023 (CCF-A, Full paper) [code]
2022
- MaxMatch: Semi-Supervised Learning with Worst-Case Consistency
Yangbangyan Jiang, Xiaodan Li, Yuefeng Chen, Yuan He, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang
IEEE TPAMI 2022 (CCF-A, Regular paper) [pdf] [code]
- Not All Samples are Trustworthy: Towards Deep Robust SVP Prediction
Qianqian Xu, Zhiyong Yang, Yangbangyan Jiang, Xiaochun Cao, Yuan Yao and Qingming Huang
IEEE TPAMI 2022 (CCF-A, Regular paper) [pdf] [code]
- Dist-PU: Positive-Unlabeled Learning from a Label Distribution Perspective
Yunrui Zhao, Qianqian Xu, Yangbangyan Jiang, Peisong Wen and Qingming Huang
CVPR 2022 (CCF-A) [pdf] [supp] [code]
- Pay Attention to Your Positive Pairs: Positive Pair Aware Contrastive Knowledge Distillation
Zhipeng Yu, Qianqian Xu, Yangbangyan Jiang, Haoyu Qin and Qingming Huang
ACM MM 2022 (CCF-A, Full paper) [pdf] [code]
2021
- What to Select: Pursuing Consistent Motion Segmentation from Multiple Geometric Models
Yangbangyan Jiang, Qianqian Xu, Ke Ma, Zhiyong Yang, Xiaochun Cao and Qingming Huang
AAAI 2021 (CCF-A) [pdf] [code] [supp]
- Seeking the Shape of Sound: An Adaptive Framework for Learning Voice-Face Association
Peisong Wen, Qianqian Xu, Yangbangyan Jiang, Zhiyong Yang, Yuan He and Qingming Huang
CVPR 2021 (CCF-A) [pdf] [code]
- Deep Partial Rank Aggregation for Personalized Attributes
Qianqian Xu, Zhiyong Yang, Zuyao Chen, Yangbangyan Jiang, Xiaochun Cao, Yuan Yao and Qingming Huang
AAAI 2021 (CCF-A) [pdf] [code]
2020
2019
- DM2C: Deep Mixed-Modal Clustering
Yangbangyan Jiang, Qianqian Xu, Zhiyong Yang, Xiaochun Cao and Qingming Huang
NeurIPS 2019 (CCF-A, Spotlight, Acceptance Rate = 2.4%) [code] [poster] [slides]
- Generalized Block-Diagonal Structure Pursuit: Learning Soft Latent Task Assignment against Negative Transfer
Zhiyong Yang, Qianqian Xu, Yangbangyan Jiang, Xiaochun Cao and Qingming Huang
NeurIPS 2019 (CCF-A, Poster)
- Deep Robust Subjective Visual Property Prediction in Crowdsourcing
Qianqian Xu, Zhiyong Yang, Yangbangyan Jiang, Xiaochun Cao, Qingming Huang and Yuan Yao
CVPR 2019 (CCF-A, Poster) [pdf] [code]
- Duet Robust Deep Subspace Clustering
Yangbangyan Jiang, Qianqian Xu, Zhiyong Yang, Xiaochun Cao and Qingming Huang
ACM MM 2019 (CCF-A, Full paper) [pdf] [code]
- Adversarial Preference Learning with Pairwise Comparisons
Zitai Wang, Qianqian Xu, Ke Ma, Yangbangyan Jiang, Xiaochun Cao and Qingming Huang
ACM MM 2019 (CCF-A, Oral) [pdf] [code]
2018
- When to Learn What: Deep Cognitive Subspace Clustering
Yangbangyan Jiang, Zhiyong Yang, Qianqian Xu, Xiaochun Cao and Qingming Huang
ACM MM 2018 (CCF-A, Full paper) [pdf] [code]
- Who to Ask: An Intelligent Fashion Consultant
Yangbangyan Jiang, Qianqian Xu, Xiaochun Cao and Qingming Huang
ICMR 2018 (CCF-B, Demo paper, Best demo runner-up)