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ORCIDGuansong Pang
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- affiliation: Singapore Management University
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2020 – today
- 2024
[j27]Rongrong Ma
, Guansong Pang, Ling Chen:
Harnessing collective structure knowledge in data augmentation for graph neural networks. Neural Networks 180: 106651 (2024)- [j26]Kexin Zhang, Qingsong Wen, Chaoli Zhang, Rongyao Cai, Ming Jin, Yong Liu, James Y. Zhang, Yuxuan Liang, Guansong Pang, Dongjin Song, Shirui Pan:
Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects. IEEE Trans. Pattern Anal. Mach. Intell. 46(10): 6775-6794 (2024) - [j25]Tianqi Li, Guansong Pang, Xiao Bai, Jin Zheng, Lei Zhou, Xin Ning:
Learning adversarial semantic embeddings for zero-shot recognition in open worlds. Pattern Recognit. 149: 110258 (2024) - [j24]Hongzuo Xu, Yijie Wang, Songlei Jian, Qing Liao, Yongjun Wang, Guansong Pang:
Calibrated One-Class Classification for Unsupervised Time Series Anomaly Detection. IEEE Trans. Knowl. Data Eng. 36(11): 5723-5736 (2024) - [j23]Chaoxi Niu, Guansong Pang, Ling Chen:
Affinity Uncertainty-Based Hard Negative Mining in Graph Contrastive Learning. IEEE Trans. Neural Networks Learn. Syst. 35(9): 11681-11691 (2024) - [c59]Ruohuan Fang, Guansong Pang, Xiao Bai:
Simple Image-Level Classification Improves Open-Vocabulary Object Detection. AAAI 2024: 1716-1725 - [c58]Wenjun Miao, Guansong Pang, Xiao Bai, Tianqi Li, Jin Zheng:
Out-of-Distribution Detection in Long-Tailed Recognition with Calibrated Outlier Class Learning. AAAI 2024: 4216-4224 - [c57]Peng Wu, Xuerong Zhou, Guansong Pang, Lingru Zhou, Qingsen Yan, Peng Wang, Yanning Zhang:
VadCLIP: Adapting Vision-Language Models for Weakly Supervised Video Anomaly Detection. AAAI 2024: 6074-6082 - [c56]Tianqi Li, Guansong Pang, Xiao Bai, Wenjun Miao, Jin Zheng:
Learning Transferable Negative Prompts for Out-of-Distribution Detection. CVPR 2024: 17584-17594 - [c55]Jiawen Zhu, Choubo Ding, Yu Tian, Guansong Pang:
Anomaly Heterogeneity Learning for Open-Set Supervised Anomaly Detection. CVPR 2024: 17616-17626 - [c54]Jiawen Zhu, Guansong Pang:
Toward Generalist Anomaly Detection via In-Context Residual Learning with Few-Shot Sample Prompts. CVPR 2024: 17826-17836 - [c53]Peng Wu, Xuerong Zhou, Guansong Pang, Yujia Sun, Jing Liu, Peng Wang, Yanning Zhang:
Open-Vocabulary Video Anomaly Detection. CVPR 2024: 18297-18307 - [c52]Chaoxi Niu, Guansong Pang, Ling Chen:
Graph Continual Learning with Debiased Lossless Memory Replay. ECAI 2024: 1808-1815 - [c51]Yuting Sun, Guansong Pang, Guanhua Ye, Tong Chen, Xia Hu, Hongzhi Yin:
Unraveling the 'Anomaly' in Time Series Anomaly Detection: A Self-supervised Tri-domain Solution. ICDE 2024: 981-994 - [c50]Qihang Zhou, Guansong Pang, Yu Tian, Shibo He, Jiming Chen:
AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection. ICLR 2024 - [c49]Choubo Ding, Guansong Pang:
Zero-Shot Out-of-Distribution Detection with Outlier Label Exposure. IJCNN 2024: 1-8 - [c48]Rongrong Ma, Guansong Pang, Ling Chen:
Imbalanced Graph Classification with Multi-scale Oversampling Graph Neural Networks. IJCNN 2024: 1-8 - [c47]Feiyi Chen, Yingying Zhang, Lunting Fan, Yuxuan Liang, Guansong Pang, Qingsong Wen, Shuiguang Deng:
Cluster-Wide Task Slowdown Detection in Cloud System. KDD 2024: 266-277 - [c46]Choubo Ding, Guansong Pang:
Improving Out-of-Distribution Detection with Disentangled Foreground and Background Features. ACM Multimedia 2024: 8923-8931 - [c45]Peng Wu, Xuerong Zhou, Guansong Pang, Zhiwei Yang, Qingsen Yan, Peng Wang, Yanning Zhang:
Weakly Supervised Video Anomaly Detection and Localization with Spatio-Temporal Prompts. ACM Multimedia 2024: 9301-9310 - [c44]Yutong Chen, Hongzuo Xu, Guansong Pang, Hezhe Qiao, Yuan Zhou, Mingsheng Shang:
Self-supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection. ECML/PKDD (6) 2024: 145-162 - [c43]Feiyi Chen, Zhen Qin, Mengchu Zhou, Yingying Zhang, Shuiguang Deng, Lunting Fan, Guansong Pang, Qingsong Wen:
LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Time Series Anomaly Detection. WWW 2024: 4138-4149 - [i69]Yunkang Cao, Xiaohao Xu, Jiangning Zhang, Yuqi Cheng, Xiaonan Huang, Guansong Pang, Weiming Shen:
A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect. CoRR abs/2401.16402 (2024) - [i68]Hezhe Qiao, Qingsong Wen, Xiaoli Li, Ee-Peng Lim, Guansong Pang:
Generative Semi-supervised Graph Anomaly Detection. CoRR abs/2402.11887 (2024) - [i67]Jiawen Zhu, Guansong Pang:
Toward Generalist Anomaly Detection via In-context Residual Learning with Few-shot Sample Prompts. CoRR abs/2403.06495 (2024) - [i66]Yukun Li, Guansong Pang, Wei Suo, Chenchen Jing, Yuling Xi, Lingqiao Liu, Hao Chen, Guoqiang Liang, Peng Wang:
CoLeCLIP: Open-Domain Continual Learning via Joint Task Prompt and Vocabulary Learning. CoRR abs/2403.10245 (2024) - [i65]Tianqi Li, Guansong Pang, Xiao Bai, Wenjun Miao, Jin Zheng:
Learning Transferable Negative Prompts for Out-of-Distribution Detection. CoRR abs/2404.03248 (2024) - [i64]Jiangning Zhang, Chengjie Wang, Xiangtai Li, Guanzhong Tian, Zhucun Xue, Yong Liu, Guansong Pang, Dacheng Tao:
Learning Feature Inversion for Multi-class Anomaly Detection under General-purpose COCO-AD Benchmark. CoRR abs/2404.10760 (2024) - [i63]Chaoxi Niu, Guansong Pang, Ling Chen:
Graph Continual Learning with Debiased Lossless Memory Replay. CoRR abs/2404.10984 (2024) - [i62]Rongrong Ma, Guansong Pang, Ling Chen:
Imbalanced Graph Classification with Multi-scale Oversampling Graph Neural Networks. CoRR abs/2405.04903 (2024) - [i61]Rongrong Ma, Guansong Pang, Ling Chen:
Harnessing Collective Structure Knowledge in Data Augmentation for Graph Neural Networks. CoRR abs/2405.10633 (2024) - [i60]Choubo Ding, Guansong Pang:
Zero-Shot Out-of-Distribution Detection with Outlier Label Exposure. CoRR abs/2406.01170 (2024) - [i59]Yutong Chen, Hongzuo Xu, Guansong Pang, Hezhe Qiao, Yuan Zhou, Mingsheng Shang:
Self-Supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection. CoRR abs/2406.19770 (2024) - [i58]Wenjun Miao, Guansong Pang, Trong-Tung Nguyen, Ruohang Fang, Jin Zheng, Xiao Bai:
OpenCIL: Benchmarking Out-of-Distribution Detection in Class-Incremental Learning. CoRR abs/2407.06045 (2024) - [i57]Feiyi Chen, Yingying Zhang, Lunting Fan, Yuxuan Liang, Guansong Pang, Qingsong Wen, Shuiguang Deng:
Cluster-Wide Task Slowdown Detection in Cloud System. CoRR abs/2408.04236 (2024) - [i56]Peng Wu, Xuerong Zhou, Guansong Pang, Zhiwei Yang, Qingsen Yan, Peng Wang, Yanning Zhang:
Weakly Supervised Video Anomaly Detection and Localization with Spatio-Temporal Prompts. CoRR abs/2408.05905 (2024) - [i55]Peng Wu, Chengyu Pan, Yuting Yan, Guansong Pang, Peng Wang, Yanning Zhang:
Deep Learning for Video Anomaly Detection: A Review. CoRR abs/2409.05383 (2024) - [i54]Hezhe Qiao, Hanghang Tong, Bo An, Irwin King, Charu C. Aggarwal, Guansong Pang:
Deep Graph Anomaly Detection: A Survey and New Perspectives. CoRR abs/2409.09957 (2024) - [i53]Jiawen Zhu, Yew-Soon Ong, Chunhua Shen, Guansong Pang:
Fine-grained Abnormality Prompt Learning for Zero-shot Anomaly Detection. CoRR abs/2410.10289 (2024) - [i52]Chaoxi Niu, Guansong Pang, Ling Chen, Bing Liu:
Replay-and-Forget-Free Graph Class-Incremental Learning: A Task Profiling and Prompting Approach. CoRR abs/2410.10341 (2024) - [i51]Sinong Zhao, Wenrui Wang, Hongzuo Xu, Zhaoyang Yu, Qingsong Wen, Gang Wang, Xiaoguang Liu, Guansong Pang:
Abnormality Forecasting: Time Series Anomaly Prediction via Future Context Modeling. CoRR abs/2410.12206 (2024) - [i50]Chaoxi Niu, Hezhe Qiao, Changlu Chen, Ling Chen, Guansong Pang:
Zero-shot Generalist Graph Anomaly Detection with Unified Neighborhood Prompts. CoRR abs/2410.14886 (2024) - [i49]Wenjun Miao, Guansong Pang, Jin Zheng, Xiao Bai:
Long-Tailed Out-of-Distribution Detection via Normalized Outlier Distribution Adaptation. CoRR abs/2410.20807 (2024) - 2023
- [j22]Hongzuo Xu, Yijie Wang, Guansong Pang, Songlei Jian, Ning Liu, Yongjun Wang:
RoSAS: Deep semi-supervised anomaly detection with contamination-resilient continuous supervision. Inf. Process. Manag. 60(5): 103459 (2023) - [j21]Yu Tian, Fengbei Liu, Guansong Pang, Yuanhong Chen, Yuyuan Liu, Johan W. Verjans, Rajvinder Singh, Gustavo Carneiro:
Self-supervised pseudo multi-class pre-training for unsupervised anomaly detection and segmentation in medical images. Medical Image Anal. 90: 102930 (2023) - [j20]Jiaying Liu, Feng Xia, Jing Ren, Bo Xu, Guansong Pang, Lianhua Chi:
MIRROR: Mining Implicit Relationships via Structure-Enhanced Graph Convolutional Networks. ACM Trans. Knowl. Discov. Data 17(4): 55:1-55:24 (2023) - [j19]Hongzuo Xu, Guansong Pang, Yijie Wang, Yongjun Wang:
Deep Isolation Forest for Anomaly Detection. IEEE Trans. Knowl. Data Eng. 35(12): 12591-12604 (2023) - [c42]Qizhou Wang, Guansong Pang, Mahsa Salehi, Wray L. Buntine, Christopher Leckie:
Cross-Domain Graph Anomaly Detection via Anomaly-Aware Contrastive Alignment. AAAI 2023: 4676-4684 - [c41]Haoyu Wang, Guansong Pang, Peng Wang, Lei Zhang, Wei Wei, Yanning Zhang:
Glocal Energy-based Learning for Few-Shot Open-Set Recognition. CVPR 2023: 7507-7516 - [c40]Jiaxi Li, Guansong Pang, Ling Chen, Mohammad-Reza Namazi-Rad:
HRGCN: Heterogeneous Graph-level Anomaly Detection with Hierarchical Relation-augmented Graph Neural Networks. DSAA 2023: 1-10 - [c39]Yuyuan Liu, Choubo Ding, Yu Tian, Guansong Pang, Vasileios Belagiannis, Ian D. Reid, Gustavo Carneiro:
Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation. ICCV 2023: 1151-1161 - [c38]Cheng Yan, Shiyu Zhang, Yang Liu, Guansong Pang, Wenjun Wang:
Feature Prediction Diffusion Model for Video Anomaly Detection. ICCV 2023: 5504-5514 - [c37]Tri Cao, Jiawen Zhu, Guansong Pang:
Anomaly Detection under Distribution Shift. ICCV 2023: 6488-6500 - [c36]Guansong Pang, Chunhua Shen, Huidong Jin, Anton van den Hengel:
Deep Weakly-supervised Anomaly Detection. KDD 2023: 1795-1807 - [c35]Yu Tian, Guansong Pang, Yuyuan Liu, Chong Wang, Yuanhong Chen, Fengbei Liu, Rajvinder Singh, Johan W. Verjans, Mengyu Wang, Gustavo Carneiro:
Unsupervised Anomaly Detection in Medical Images with a Memory-Augmented Multi-level Cross-Attentional Masked Autoencoder. MLMI@MICCAI (2) 2023: 11-21 - [c34]Hezhe Qiao, Guansong Pang:
Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection. NeurIPS 2023 - [c33]Chaoxi Niu, Guansong Pang, Ling Chen:
Graph-Level Anomaly Detection via Hierarchical Memory Networks. ECML/PKDD (1) 2023: 201-218 - [c32]Zhong Zhuang, Kai Ming Ting, Guansong Pang, Shuaibin Song:
Subgraph Centralization: A Necessary Step for Graph Anomaly Detection. SDM 2023: 703-711 - [c31]Qing Li, Xiao Huang, Ninghao Liu, Yuxiao Dong, Guansong Pang:
International Workshop on Learning with Knowledge Graphs: Construction, Embedding, and Reasoning. WSDM 2023: 1273-1274 - [i48]Zhong Zhuang, Kai Ming Ting, Guansong Pang, Shuaibin Song:
Subgraph Centralization: A Necessary Step for Graph Anomaly Detection. CoRR abs/2301.06794 (2023) - [i47]Chaoxi Niu, Guansong Pang, Ling Chen:
Affinity Uncertainty-based Hard Negative Mining in Graph Contrastive Learning. CoRR abs/2301.13340 (2023) - [i46]Choubo Ding, Guansong Pang, Chunhua Shen:
Background Matters: Enhancing Out-of-distribution Detection with Domain Features. CoRR abs/2303.08727 (2023) - [i45]Tri Cao, Jiawen Zhu, Guansong Pang:
Anomaly Detection under Distribution Shift. CoRR abs/2303.13845 (2023) - [i44]Haoyu Wang, Guansong Pang, Peng Wang, Lei Zhang, Wei Wei, Yanning Zhang:
Glocal Energy-based Learning for Few-Shot Open-Set Recognition. CoRR abs/2304.11855 (2023) - [i43]Hezhe Qiao, Guansong Pang:
Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection. CoRR abs/2306.00006 (2023) - [i42]Kexin Zhang, Qingsong Wen, Chaoli Zhang, Rongyao Cai, Ming Jin, Yong Liu, James Zhang, Yuxuan Liang, Guansong Pang, Dongjin Song, Shirui Pan:
Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects. CoRR abs/2306.10125 (2023) - [i41]Chaoxi Niu, Guansong Pang, Ling Chen:
Graph-level Anomaly Detection via Hierarchical Memory Networks. CoRR abs/2307.00755 (2023) - [i40]Tianqi Li, Guansong Pang, Xiao Bai, Jin Zheng, Lei Zhou, Xin Ning:
Learning Adversarial Semantic Embeddings for Zero-Shot Recognition in Open Worlds. CoRR abs/2307.03416 (2023) - [i39]Hongzuo Xu, Yijie Wang, Guansong Pang, Songlei Jian, Ning Liu, Yongjun Wang:
RoSAS: Deep Semi-Supervised Anomaly Detection with Contamination-Resilient Continuous Supervision. CoRR abs/2307.13239 (2023) - [i38]Peng Wu, Xuerong Zhou, Guansong Pang, Lingru Zhou, Qingsen Yan, Peng Wang, Yanning Zhang:
VadCLIP: Adapting Vision-Language Models for Weakly Supervised Video Anomaly Detection. CoRR abs/2308.11681 (2023) - [i37]Jiaxi Li, Guansong Pang, Ling Chen, Mohammad-Reza Namazi-Rad:
HRGCN: Heterogeneous Graph-level Anomaly Detection with Hierarchical Relation-augmented Graph Neural Networks. CoRR abs/2308.14340 (2023) - [i36]Ruohuan Fang, Guansong Pang, Lei Zhou, Xiao Bai, Jin Zheng:
Unsupervised Recognition of Unknown Objects for Open-World Object Detection. CoRR abs/2308.16527 (2023) - [i35]Feiyi Chen, Zhen Qing, Yingying Zhang, Shuiguang Deng, Yi Xiao, Guansong Pang, Qingsong Wen:
LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Anomaly Detection. CoRR abs/2310.05668 (2023) - [i34]Jiawen Zhu, Choubo Ding, Yu Tian, Guansong Pang:
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection. CoRR abs/2310.12790 (2023) - [i33]Qihang Zhou, Guansong Pang, Yu Tian, Shibo He, Jiming Chen:
AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection. CoRR abs/2310.18961 (2023) - [i32]Qizhou Wang, Guansong Pang, Mahsa Salehi, Wray L. Buntine, Christopher Leckie:
Open-Set Graph Anomaly Detection via Normal Structure Regularisation. CoRR abs/2311.06835 (2023) - [i31]Peng Wu, Xuerong Zhou, Guansong Pang, Yujia Sun, Jing Liu, Peng Wang, Yanning Zhang:
Open-Vocabulary Video Anomaly Detection. CoRR abs/2311.07042 (2023) - [i30]Yuting Sun, Guansong Pang, Guanhua Ye, Tong Chen, Xia Hu, Hongzhi Yin:
Unraveling the "Anomaly" in Time Series Anomaly Detection: A Self-supervised Tri-domain Solution. CoRR abs/2311.11235 (2023) - [i29]Ruohuan Fang, Guansong Pang, Xiao Bai:
Simple Image-level Classification Improves Open-vocabulary Object Detection. CoRR abs/2312.10439 (2023) - [i28]Wenjun Miao, Guansong Pang, Tianqi Li, Xiao Bai, Jin Zheng:
Out-of-Distribution Detection in Long-Tailed Recognition with Calibrated Outlier Class Learning. CoRR abs/2312.10686 (2023) - 2022
- [j18]Guansong Pang, Chunhua Shen, Longbing Cao, Anton van den Hengel:
Deep Learning for Anomaly Detection: A Review. ACM Comput. Surv. 54(2): 38:1-38:38 (2022) - [j17]Guansong Pang:
AI in Beijing 2022 Olympic Winter Games. IEEE Intell. Syst. 37(1): 110 (2022) - [j16]Guansong Pang:
The AI Chip Race. IEEE Intell. Syst. 37(2): 111-112 (2022) - [j15]Guansong Pang:
Artificial Intelligence for Natural Disaster Management. IEEE Intell. Syst. 37(6): 3-6 (2022) - [j14]Xiaoyu Xu, Guansong Pang, Di Wu, Mingsheng Shang:
Joint hyperbolic and Euclidean geometry contrastive graph neural networks. Inf. Sci. 609: 799-815 (2022) - [j13]Qing Li, Guansong Pang, Mingsheng Shang:
An efficient annealing-assisted differential evolution for multi-parameter adaptive latent factor analysis. J. Big Data 9(1): 95 (2022) - [j12]Cheng Yan, Guansong Pang, Xiao Bai, Changhong Liu, Xin Ning, Lin Gu, Jun Zhou:
Beyond Triplet Loss: Person Re-Identification With Fine-Grained Difference-Aware Pairwise Loss. IEEE Trans. Multim. 24: 1665-1677 (2022) - [j11]Guansong Pang, Charu Aggarwal, Chunhua Shen, Nicu Sebe:
Editorial Deep Learning for Anomaly Detection. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2282-2286 (2022) - [c30]Yuanhong Chen, Yu Tian, Guansong Pang, Gustavo Carneiro:
Deep One-Class Classification via Interpolated Gaussian Descriptor. AAAI 2022: 383-392 - [c29]Choubo Ding, Guansong Pang, Chunhua Shen:
Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection. CVPR 2022: 7378-7388 - [c28]Yu Tian, Yuyuan Liu, Guansong Pang, Fengbei Liu, Yuanhong Chen, Gustavo Carneiro:
Pixel-Wise Energy-Biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes. ECCV (39) 2022: 246-263 - [c27]Guansong Pang, Jundong Li, Anton van den Hengel, Longbing Cao, Thomas G. Dietterich:
ANDEA: Anomaly and Novelty Detection, Explanation, and Accommodation. KDD 2022: 4892-4893 - [c26]Yu Tian, Guansong Pang, Fengbei Liu, Yuyuan Liu, Chong Wang, Yuanhong Chen, Johan Verjans, Gustavo Carneiro:
Contrastive Transformer-Based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection. MICCAI (3) 2022: 88-98 - [c25]Guansong Pang, Ngoc Thien Anh Pham, Emma Baker, Rebecca Bentley, Anton van den Hengel:
Deep Depression Prediction on Longitudinal Data via Joint Anomaly Ranking and Classification. PAKDD (2) 2022: 236-248 - [c24]Rongrong Ma, Guansong Pang, Ling Chen, Anton van den Hengel:
Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation. WSDM 2022: 704-714 - [i27]Jitendra Singh Malik, Guansong Pang, Anton van den Hengel:
Deep Learning for Hate Speech Detection: A Comparative Study. CoRR abs/2202.09517 (2022) - [i26]Yu Tian, Guansong Pang, Yuyuan Liu, Chong Wang, Yuanhong Chen, Fengbei Liu, Rajvinder Singh, Johan W. Verjans, Gustavo Carneiro:
Unsupervised Anomaly Detection in Medical Images with a Memory-augmented Multi-level Cross-attentional Masked Autoencoder. CoRR abs/2203.11725 (2022) - [i25]Yu Tian, Guansong Pang, Fengbei Liu, Yuyuan Liu, Chong Wang, Yuanhong Chen, Johan W. Verjans, Gustavo Carneiro:
Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection. CoRR abs/2203.12121 (2022) - [i24]Choubo Ding, Guansong Pang, Chunhua Shen:
Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection. CoRR abs/2203.14506 (2022) - [i23]Hongzuo Xu, Guansong Pang, Yijie Wang, Yongjun Wang:
Deep Isolation Forest for Anomaly Detection. CoRR abs/2206.06602 (2022) - [i22]Hongzuo Xu, Yijie Wang, Songlei Jian, Qing Liao, Yongjun Wang, Guansong Pang:
Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection. CoRR abs/2207.12201 (2022) - [i21]Yuyuan Liu, Choubo Ding, Yu Tian, Guansong Pang, Vasileios Belagiannis, Ian D. Reid, Gustavo Carneiro:
Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation. CoRR abs/2211.14512 (2022) - [i20]Qizhou Wang, Guansong Pang, Mahsa Salehi, Wray L. Buntine, Christopher Leckie:
Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive Alignment. CoRR abs/2212.01096 (2022) - 2021
- [j10]Guansong Pang, Longbing Cao, Ling Chen:
Homophily outlier detection in non-IID categorical data. Data Min. Knowl. Discov. 35(4): 1163-1224 (2021) - [j9]Guansong Pang, Fabrizio Angiulli, Mihai Cucuringu, Huan Liu:
Guest Editorial: Non-IID Outlier Detection in Complex Contexts. IEEE Intell. Syst. 36(3): 3-4 (2021) - [j8]Jianpeng Zhang, Yutong Xie, Guansong Pang, Zhibin Liao, Johan Verjans, Wenxing Li, Zongji Sun, Jian He, Yi Li, Chunhua Shen, Yong Xia:
Viral Pneumonia Screening on Chest X-Rays Using Confidence-Aware Anomaly Detection. IEEE Trans. Medical Imaging 40(3): 879-890 (2021) - [c23]Yu Tian, Guansong Pang, Yuanhong Chen, Rajvinder Singh, Johan W. Verjans, Gustavo Carneiro:
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning. ICCV 2021: 4955-4966 - [c22]Cheng Yan, Guansong Pang, Lei Wang, Jile Jiao, Xuetao Feng, Chunhua Shen, Jingjing Li:
BV-Person: A Large-scale Dataset for Bird-view Person Re-identification. ICCV 2021: 10923-10932 - [c21]Cheng Yan, Guansong Pang, Jile Jiao, Xiao Bai, Xuetao Feng, Chunhua Shen:
Occluded Person Re-Identification with Single-scale Global Representations. ICCV 2021: 11855-11864 - [c20]Guansong Pang, Anton van den Hengel, Chunhua Shen, Longbing Cao:
Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data. KDD 2021: 1298-1308 - [c19]Guansong Pang, Charu C. Aggarwal:
Toward Explainable Deep Anomaly Detection. KDD 2021: 4056-4057 - [c18]Guansong Pang, Jundong Li, Anton van den Hengel, Longbing Cao, Thomas G. Dietterich:
Anomaly and Novelty Detection, Explanation, and Accommodation (ANDEA). KDD 2021: 4145-4146 - [c17]Yu Tian, Guansong Pang, Fengbei Liu, Yuanhong Chen, Seon-Ho Shin, Johan W. Verjans, Rajvinder Singh, Gustavo Carneiro:
Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images. MICCAI (5) 2021: 128-140 - [c16]Guansong Pang, Longbing Cao, Charu Aggarwal:
Deep Learning for Anomaly Detection: Challenges, Methods, and Opportunities. WSDM 2021: 1127-1130 - [i19]Yu Tian, Guansong Pang, Yuanhong Chen, Rajvinder Singh, Johan W. Verjans, Gustavo Carneiro:
Weakly-supervised Video Anomaly Detection with Contrastive Learning of Long and Short-range Temporal Features. CoRR abs/2101.10030 (2021) - [i18]