Publications

[Google Scholar], [Legacy Homepage]

[27] Action Co-Localization in an Untrimmed Video by Graph Neural Networks

Changbo Zhai, Le Wang, Qilin Zhang, Zhanning Gao, Zhenxing Niu, Nanning Zheng, Gang Hua, “Action Co-Localization in an Untrimmed Video by Graph Neural Networks”, in Proc. 26th International Conference On Multimedia Modeling (MMM 2020), Daejeon, Korea, Jan. 5-8, 2020.

[26] Weakly Supervised Temporal Action Localization through Contrast based Evaluation Networks

Ziyi Liu, Le Wang, Qilin Zhang, Zhanning Gao, Zhenxing Niu, Nanning Zheng, Gang Hua, “Weakly Supervised Temporal Action Localization through Contrast based Evaluation Networks”, in Proc. IEEE International Conference in Computer Vision (ICCV 2019), Seoul, Korea, Oct. 27-Nov. 2, 2019. [PDF], [BibTex]

[25] Action Coherence Network for Weakly Supervised Temporal Action Localization

Yuanhao Zhai, Le Wang, Ziyi Liu, Qilin Zhang, Gang Hua, and Nanning Zheng, “Action Coherence Network for Weakly Supervised Temporal Action Localization”, in Proc. IEEE International Conference on Image Processing (ICIP’2019), Taipei, September 22-25, 2019. [Link], [PDF], [BibTeX]

[24] Object Affordances Graph Network for Action Recognition

Haoliang Tan, Le Wang, Qilin Zhang, Zhanning Gao, Nanning Zheng, and Gang Hua, “Object Affordances Graph Network for Action Recognition”, in Proc. 30th British Machine Vision Conference, BMVC 2019, Cardiff University, Cardiff, UK, September 9-12, 2019. (Spotlight) [Link], [PDF], [BibTeX]

[23] Extracting Action Sensitive Features to Facilitate Weakly-supervised Action Localization

Zijian Kang, Le Wang, Ziyi Liu, Qilin Zhang, and Nanning Zheng, “Extracting Action Sensitive Features to Facilitate Weakly-supervised Action Localization”, In Proceedings of the 15th International Conference on Artificial Intelligence Applications and Innovations (AIAI’2019), May 24-26, 2019, Crete, Greece. [Link], [PDF], [BibTeX]

[22] Video Imprint Segmentation for Temporal Action Detection in Untrimmed Videos

Zhanning Gao, Le Wang, Qilin Zhang, Zhenxing Niu, Nanning Zheng, and Gang Hua, “Video Imprint Segmentation for Temporal Action Detection in Untrimmed Videos”, In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-19), January 27 - February 1, 2019, Honolulu, Hawaii, USA. (oral presentation) [Link], [PDF], [BibTex]

[21] Convolutional Neural Networks with Generalized Attentional Pooling for Action Recognition

Yunfeng Wang, Wengang Zhou, Qilin Zhang, Houqiang Li, “Convolutional Neural Networks with Generalized Attentional Pooling for Action Recognition”, IEEE International Conference on Visual Communications and Image Processing (VCIP), December 2018. (oral presentation) [Link], [PDF], [BibTex]

[20] Video Object Co-segmentation from Noisy Videos by a Multi-level Hypergraph Model

Lv, Xin, Le Wang, Qilin Zhang, Nanning Zheng, and Gang Hua. “Video Object Co-segmentation from Noisy Videos by a Multi-level Hypergraph Model”, in Proc. IEEE International Conference on Image Processing (ICIP’2018), Athens, Greece, October, 2018. [Link], [PDF], [BibTeX]

[19] Joint Spatio-temporal Action Localization in Untrimmed Videos with Per-frame Segmentation

Duan, Xuhuan, Le Wang, Changbo Zhai, Nanning Zheng, Qilin Zhang, Zhenzing Niu, and Gang Hua. “Joint Spatio-temporal Action Localization in Untrimmed Videos with Per-frame Segmentation”, in Proc. IEEE International Conference on Image Processing (ICIP’2018), Athens, Greece, October, 2018. (oral presentation) [Link], [PDF], [BibTeX]

[18] Joint Video Object Discovery and Segmentation by Coupled Dynamic Markov Networks

Ziyi Liu, Le Wang, Gang Hua, Qilin Zhang, Zhenxing Niu, Ying Wu, Nanning Zheng, “Joint Video Object Discovery and Segmentation by Coupled Dynamic Markov Networks”, IEEE Transactions on Image Processing, vol. 27, no. 12, pp. 5840-5853, Dec. 2018. [Link], [PDF], [BibTeX]

[17] Weighted Multi-Region Convolutional Neural Network for Action Recognition with Low-Latency Online Prediction

Wang, Yunfeng, Wengang Zhou, Qilin Zhang, Xiaotian Zhu, and Houqiang Li. “Weighted Multi-Region Convolutional Neural Network for Action Recognition with Low-Latency Online Prediction”, in Proc. IEEE International Conference on Multimedia and Expo (ICME), Workshops, San Diego, USA, July 2018. [Link], [PDF], [extended arXiv], [BibTeX]

[16] Enhanced Action Recognition with Visual Attribute-augmented 3D Convolutional Neural Network

Wang, Yunfeng, Wengang Zhou, Qilin Zhang, and Houqiang Li. “Enhanced Action Recognition with Visual Attribute-augmented 3D Convolutional Neural Network”, in Proc. IEEE International Conference on Multimedia and Expo (ICME), Industry Program, San Diego, USA, July 2018. [Link], [PDF], [extended arXiv], [BibTeX]

[15] Traffic Sensory Data Classification by Quantifying Scenario Complexity

Wang, Jiajie, Chi Zhang, Yuehu Liu, and Qilin Zhang. “Traffic Sensory Data Classification by Quantifying Scenario Complexity”, in Proc. IEEE Intelligent Vehicles Symposium (IV’2018), Changshu, China, June, 2018. [Link], [PDF], [BibTeX]

[14] Multi-model Traffic Scene Simulation with Road Image Sequences and GIS Information

Cui, Zhichao, Yuehu Liu, Fuji Ren, and Qilin Zhang. “Multi-model Traffic Scene Simulation with Road Image Sequences and GIS Information”, in Proc. IEEE Intelligent Vehicles Symposium (IV’2018), Changshu, China, June, 2018. [Link], [PDF], [BibTeX]

[13] A Graded Offline Evaluation Framework for Intelligent Vehicle’s Cognitive Ability

Zhang, Chi, Yuehu Liu, Qilin Zhang, and Le Wang, “A Graded Offline Evaluation Framework for Intelligent Vehicle’s Cognitive Ability”, in Proc. IEEE Intelligent Vehicles Symposium (IV’2018), Changshu, China, June, 2018. (oral presentation) [Link], [PDF], [BibTeX]

[12] Action Recognition by an Attention-Aware Temporal Weighted Convolutional Neural Network

Wang, Le, Jinliang Zang, Qilin Zhang, Zhenxing Niu, Gang Hua, and Nanning Zheng, “Action Recognition by an Attention-Aware Temporal Weighted Convolutional Neural Network”, Sensors 18, no. 7 (2018): 1979. [Link], [PDF], [BibTeX]

[11] Attention-based Temporal Weighted Convolutional Neural Network for Action Recognition

Zang, Jinliang, Le Wang, Ziyi Liu, Qilin Zhang, Zhenxing Niu, Gang Hua, and Nanning Zheng. “Attention-based Temporal Weighted Convolutional Neural Network for Action Recognition.” In Proceedings of the 14th International Conference on Artificial Intelligence Applications and Innovations (AIAI’2018), May 25-27, 2018, Rhodes, Greece. [Link], [PDF], [arXiv], [BibTeX]

[10] Segment-Tube: Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation

Wang, Le, Xuhuan Duan, Qilin Zhang, Zhenxing Niu, Gang Hua, and Nanning Zheng, “Segment-Tube: Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation”, Sensors 18, no. 5 (2018): 1657. [Link], [PDF], [BibTeX]

[9] Video-based Sign Language Recognition without Temporal Segmentation

Huang, Jie, Wengang Zhou, Qilin Zhang, Houqiang Li, and Weiping Li “Video-based Sign Language Recognition without Temporal Segmentation.” In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), Feb. 2-7, 2018, New Orleans, Louisiana, USA. [Link], [arXiv], [PDF], [BibTeX]

[8] A Hyperspectral Image Classification Framework with Spatial Pixel Pair Features

Ran, Lingyan, Yanning Zhang, Wei Wei, and Qilin Zhang. “A Hyperspectral Image Classification Framework with Spatial Pixel Pair Features.” Sensors 17, no. 10 (2017): 2421. [Link], [PDF], [BibTeX]

[7] Convolutional Neural Network-Based Robot Navigation Using Uncalibrated Spherical Images

Ran, Lingyan, Yanning Zhang, Qilin Zhang, and Tao Yang. “Convolutional Neural Network-Based Robot Navigation Using Uncalibrated Spherical Images.” Sensors 17, no. 6 (2017): 1341. [Link], [PDF], [YouTube demo], [Code Zip], [BibTeX]

[6] Auxiliary Training Information Assisted Visual Recognition

Zhang, Qilin, Gang Hua, Wei Liu, Zicheng Liu, and Zhengyou Zhang. “Auxiliary Training Information Assisted Visual Recognition.” IPSJ Transactions on Computer Vision and Applications 7 (2015): 138-150. [Link], [PDF], [BibTeX]

[5] Multi-View Visual Recognition of Imperfect Testing Data

Zhang, Qilin, and Gang Hua. “Multi-view visual recognition of imperfect testing data.” In Proceedings of the 23rd ACM international conference on Multimedia, pp. 561-570. ACM, 2015. (oral presentation) [Link], [PDF], [BibTeX]

[4] Can Visual Recognition Benefit from Auxiliary Information in Training?

Zhang, Qilin, Gang Hua, Wei Liu, Zicheng Liu, and Zhengyou Zhang. “Can visual recognition benefit from auxiliary information in training?.” In Asian Conference on Computer Vision, pp. 65-80. Springer, Cham, 2014. (oral presentation, oral acceptance rate 4%) [Link], [PDF], [Supplemental PDF], [BibTeX]

[3] Iterative Sparse Asymptotic Minimum Variance Based Approaches for Array Processing

Abeida, Habti, Qilin Zhang, Jian Li, and Nadjim Merabtine. “Iterative sparse asymptotic minimum variance based approaches for array processing.” IEEE Transactions on Signal Processing 61, no. 4 (2013): 933-944. [Link], [arXiv], [PDF], [Code Zip], [BibTeX]

[2] Fast implementation of sparse iterative covariance-based estimation for source localization

Zhang, Qilin, Habti Abeida, Ming Xue, William Rowe, and Jian Li. “Fast implementation of sparse iterative covariance-based estimation for source localization.” The Journal of the Acoustical Society of America 131, no. 2 (2012): 1249-1259. [Link], [PDF], [BixTeX], [Code Zip]

[1] Fast implementation of sparse iterative covariance-based estimation for array processing

Zhang, Qilin, Habti Abeida, Ming Xue, William Rowe, and Jian Li. “Fast implementation of sparse iterative covariance-based estimation for array processing.” In Signals, Systems and Computers (ASILOMAR), 2011 Conference Record of the Forty Fifth Asilomar Conference on, pp. 2031-2035. IEEE, 2011. [Link], [PDF], [BibTeX], [Code Zip]

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