Dr Jing Wu

2022

• Li, Z. et al. 2022. A unified understanding of deep NLP models for text classification. IEEE Transactions on Visualization and Computer Graphics 28(12), pp. 4980-4994. (10.1109/TVCG.2022.3184186)
• Grange, J. A., Princis, H., Kozlowski, T. R. W., Amadou-Dioffo, A., Wu, J., Hicks, Y. A. and Johansen, M. K. 2022. XAI & I: Self-explanatory AI facilitating mutual understanding between AI and human experts. Presented at: 26th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2022), 7-9 September 2022. Elsevier, (10.1016/j.procs.2022.09.419)
• Kong, M., Huo, J., Li, W., Wu, J., Lai, Y. and Gao, Y. 2022. Playing lottery tickets in style transfer models. Presented at: MM '22: The 30th ACM International Conference on Multimedia, 10-14 October 2022M4MM '22: Proceedings of the 1st International Workshop on Methodologies for Multimedia. New York, NY, USA: ACM pp. 15-23., (10.1145/3552487.3556440)
• Yang, X., Ji, Z., Wu, J., Lai, Y., Wei, C., Liu, G. and Setchi, R. 2022. Hierarchical reinforcement learning with universal policies for multi-step robotic manipulation. IEEE Transactions on Neural Networks and Learning Systems 33(9), pp. 4727-4741. (10.1109/TNNLS.2021.3059912)
• Xia, J. et al. 2022. Interactive visual cluster analysis by contrastive dimensionality reduction. IEEE Transactions on Visualization and Computer Graphics (10.1109/TVCG.2022.3209423)
• Yang, X., Ji, Z., Wu, J. and Lai, Y. 2022. Abstract demonstrations and adaptive exploration for efficient and stable multi-step sparse reward reinforcement learning. Presented at: 27th IEEE International Conference on Automation and Computing (ICAC2022), 1-3 September 2022.
• Chen, C., Wu, J., Wang, X., Xiang, S., Zhang, S., Tang, Q. and Liu, S. 2022. Towards better caption supervision for object detection. IEEE Transactions on Visualization and Computer Graphics 28(4), pp. 1941-1954. (10.1109/TVCG.2021.3138933)
• Wang, Z., Xie, Q., Lai, Y., Wu, J., Long, K. and Wang, J. 2022. MLVSNet: Multi-level Voting Siamese Network for 3D visual tracking. Presented at: CVF/IEEE International Conference on Computer Vision (ICCV 2021), Montreal, QC, Canada, 10-17 October 20212021 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE pp. 3081-3090., (10.1109/ICCV48922.2021.00309)
• Liang, Y., Wu, J., Lai, Y. and Qin, Y. 2022. Exploring and exploiting hubness priors for high-quality GAN latent sampling. Presented at: The 39th International Conference on Machine Learning (ICML 2022), Baltimore, Maryland USA, 17-23 July 2022, Vol. 162.

2021

• Yang, X., Ji, Z., Wu, J. and Lai, Y. 2021. An open-source multi-goal reinforcement learning environment for robotic manipulation with Pybullet. Presented at: 21st Towards Autonomous Robotic Systems Conference (TAROS 2021), Virtual, 8-10 September 2021 Presented at Fox, C. et al. eds.Towards Autonomous Robotic Systems. TAROS 2021. Lecture Notes in Computer Science Springer pp. 14-24.
• Hou, H., Huo, J., Wu, J., Lai, Y. and Gao, Y. 2021. MW-GAN: Multi-warping GAN for caricature generation with multi-style geometric exaggeration. IEEE Transactions on Image Processing 30, pp. 8644-8657. (10.1109/TIP.2021.3118984)
• Zappala, S. et al. 2021. Full-field MRI measurements of in-vivo positional brain shift reveal the significance of intra-cranial geometry and head orientation for stereotactic surgery. Scientific Reports 11(1), article number: 17684. (10.1038/s41598-021-97150-5)
• Chen, C., Wang, Z., Wu, J., Wang, X., Guo, L., Li, Y. and Liu, S. 2021. Interactive graph construction for graph-based semi-supervised learning. IEEE Transactions on Visualization and Computer Graphics 27(9), pp. 3701-3716. (10.1109/TVCG.2021.3084694)
• Xie, Q., Lai, Y., Wu, J., Wang, Z., Lu, D., Wei, M. and Wang, J. 2021. VENet: Voting Enhancement Network for 3D object detection. Presented at: CVF/IEEE International Conference on Computer Vision (ICCV 2021), Virtual, 11-17 October 2021.
• Huo, J., Jin, S., Li, W., Wu, J., Lai, Y., Shi, Y. and Gao, Y. 2021. Manifold alignment for semantically aligned style transfer. Presented at: CVF/IEEE International Conference on Computer Vision (ICCV 2021), Virtual, 11-17 October 2021.
• Cao, K., Liu, M., Su, H., Wu, J., Zhu, J. and Liu, S. 2021. Analyzing the noise robustness of deep neural networks. IEEE Transactions on Visualization and Computer Graphics 27(7), pp. 3289-3304. (10.1109/TVCG.2020.2969185)
• Xie, Q., Lai, Y., Wu, J., Wang, Z., Zhang, Y., Xu, K. and Wang, J. 2021. Vote-based 3D object detection with context modeling and SOB-3DNMS. International Journal of Computer Vision 129, pp. 1857-1874. (10.1007/s11263-021-01456-w)
• Yang, L., Wu, J., Huo, J., Lai, Y. and Gao, Y. 2021. Learning 3D face reconstruction from a single sketch. Graphical Models 115, article number: 101102. (10.1016/j.gmod.2021.101102)

2020

• Xie, Q., Lai, Y., Wu, J., Wang, Z., Zhang, Y., Xu, K. and Wang, J. 2020. MLCVNet: multi-level context VoteNet for 3D object detection. Presented at: IEEE/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, USA, 13-19 June 20202020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE pp. 10444-10453., (10.1109/CVPR42600.2020.01046)
• Xiang, S., Ye, X., Xia, J., Wu, J., Chen, Y. and Liu, S. 2020. Interactive correction of mislabeled training data. Presented at: IEEE VIS 2019, Vancouver, BC, Canada, 20-25 October 20192019 IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE, (10.1109/VAST47406.2019.8986943)

2019

• Pan, Y., Niu, Z., Wu, J. and Zhang, J. 2019. InSocialNet: Interactive visual analytics for role-event videos. Computational Visual Media 5(4), pp. 375-390. (10.1007/s41095-019-0157-9)
• Wang, X., Wang, X., Wang, C., Bai, X., Wu, J. and Hancock, E. R. 2019. Discriminative features matter: Multi-layer bilinear pooling for camera localization. Presented at: BMVC 2019: 30th British Machine Vision Conference, Cardiff, UK, 9-12 September, 2019.
• Zhang, Y., Wu, J., Ji, Z., Wei, M. and Zhang, C. 2019. Computer-assisted relief modelling: a comprehensive survey. Presented at: Eurographics Conference 2019 STARs, Genova, Italy, 6-10 May 2019.

2018

• Wu, J. and Ji, Z. 2018. Seeing the unseen: Locating objects from reflections. Presented at: 19th Towards Autonomous Robotic Systems (TAROS) Conference, Bristol, UK, 25- 27 July 2018.
• Liu, S., Xiao, J., Liu, J., Wang, X., Wu, J. and Zhu, J. 2018. Visual diagnosis of tree boosting methods. IEEE Transactions on Visualization and Computer Graphics 24(1), pp. 163-173. (10.1109/TVCG.2017.2744378)

2016

• Wu, J., Rosin, P. L., Sun, X. and Martin, R. R. 2016. Improving shape from shading with interactive Tabu search. Journal of Computer Science and Technology 31(3), pp. 488-500. (10.1007/s11390-016-1639-1)

2014

• Wu, J., Martin, R. R., Rosin, P. L., Sun, X., Lai, Y., Liu, Y. -. H. and Wallraven, C. 2014. Use of non-photorealistic rendering and photometric stereo in making bas-reliefs from photographs. Graphical Models 76(4), pp. 202-213. (10.1016/j.gmod.2014.02.002)

2013

• Wu, J. et al. 2013. Making bas-reliefs from photographs of human faces. Computer-Aided Design 45(3), pp. 671-682. (10.1016/j.cad.2012.11.002)

2012

• Zhang, L., Hancock, E. R. and Wu, J. 2012. Estimating surface characteristics and extracting features from polarisation. Presented at: Joint IAPR International Workshop, SSPR&SPR 2012, Hiroshima, Japan, November 7-9, 2012 Presented at Gimel'farb, G. et al. eds.Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshop, SSPR & SPR 2012, Hiroshima, Japan, November 7-9, 2012, Proceedings.. Lecture Notes in Computer Science Vol. 7626. Springer Berlin Heidelberg: Springer pp. 400-408., (10.1007/978-3-642-34166-3_44)

2011

• Wu, J., Smith, W. A. P. and Hancock, E. R. 2011. Gender discriminating models from facial surface normals. Pattern Recognition 44(12), pp. 2871-2886. (10.1016/j.patcog.2011.04.013)
• Kawulok, M., Wu, J. and Hancock, E. R. 2011. Supervised relevance maps for increasing the distinctiveness of facial images. Pattern Recognition 44(4), pp. 929-939. (10.1016/j.patcog.2010.10.010)
• Zhang, Z., Hancock, E. R. and Wu, J. 2011. An information theoretic approach to gender feature selection. Presented at: 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), Barcelona, Spain, 6-13 Nov 20112011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops). Piscataway, N.J.: IEEE pp. 1425-1431., (10.1109/ICCVW.2011.6130418)

2010

• Wu, J., Smith, W. A. P. and Hancock, E. R. 2010. Facial gender classification using shape-from-shading. Image and Vision Computing 28(6), pp. 1039-1048. (10.1016/j.imavis.2009.09.003)
• Wu, J., Smith, W. A. P. and Hancock, E. R. 2010. Semi-supervised feature selection for gender classification. Presented at: 9th Asian Conference on Computer Vision, Xi’an, China, 23-27 September 2009 Presented at Zha, H., Taniguchi, R. and Maybank, S. eds.Computer Vision – ACCV 2009: 9th Asian Conference on Computer Vision, Xi’an, September 23-27, 2009, Revised Selected Papers, Part II, Vol. II. Lecture Notes in Computer Science Vol. 5995. Berlin Heidelberg: Springer pp. 23-33., (10.1007/978-3-642-12304-7_3)

2009

• Wu, J., Smith, W. A. P., Hancock, E. R. and Kawulok, M. 2009. Extracting gender discriminating features from facial needle-maps. Presented at: 2009 IEEE International Conference on Image Processing (ICIP), Cairo, Egypt, 7-10 Nov 20092009 IEEE International Conference on Image Processing: Proceedings. Piscataway, NJ: IEEE pp. 2449-2452., (10.1109/ICIP.2009.5414129)

2008

• Wu, J., Smith, W. A. P. and Hancock, E. R. 2008. Supervised principal geodesic analysis on facial surface normals for gender classification. Presented at: Structural, Syntactic, and Statistical Pattern Recognition Joint IAPR International Workshop, SSPR & SPR 2008, Orlando, USA, 4-6 December 2008 Presented at da Vitoria Lobo, N. et al. eds.Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshop, SSPR & SPR 2008, Orlando, USA, December 4-6, 2008. Proceedings. Lecture Notes in Computer Science Vol. 5342. Berlin Heidelberg: Springer pp. 664-673., (10.1007/978-3-540-89689-0_70)
• Wu, J., Smith, W. A. P. and Hancock, E. 2008. Gender classification based on facial surface normals. Presented at: 19th International Conference on Pattern Recognition (ICPR 2008), Tampa, Florida, 8-11 December 200819th International Conference on Pattern Recognition (ICPR 2008). Piscataway, NJ: IEEE pp. 1-4., (10.1109/ICPR.2008.4761056)
• Wu, J., Smith, W. and Hancock, E. 2008. Gender classification based on facial surface normals. Presented at: International Conference on Pattern Recognition, Tampa, FL., 8-11 Dec 200819th International Conference on Pattern Recognition : (ICPR 2008) ; Tampa, Florida, USA 8-11 December 2008.. Piscataway, N.J.: IEEE pp. 1-4., (10.1109/ICPR.2008.4761056)
• Wu, J., Smith, W. A. P. and Hancock, E. R. 2008. Facial gender classification using shape from shading and weighted principal geodesic analysis. Presented at: 5th International Conference, ICIAR 2008, Póvoa de Varzim, Portugal, 25-27 June 2008 Presented at Campilho, A. and Kamel, M. eds.Image Analysis and Recognition: 5th International Conference, ICIAR 2008, Póvoa de Varzim, Portugal, June 25-27, 2008. Proceedings.. Lecture Notes in Computer Science Vol. 5112. Berlin Heidelberg: Springer pp. 925-934., (10.1007/978-3-540-69812-8_92)
• Wu, J., Smith, W. A. P. and Hancock, E. R. 2008. Weighted principal geodesic analysis for facial gender classification. Presented at: 12th Iberoamericann Congress on Pattern Recognition, CIARP 2007, Valparaiso, Chile, 13-16 November 2007 Presented at Rueda, L., Mery, D. and Kittler, J. eds.Progress in Pattern Recognition, Image Analysis and Applications: 12th Iberoamericann Congress on Pattern Recognition, CIARP 2007, Valparaiso, Chile, November 13-16, 2007. Proceedings.. Lecture Notes in Computer Science Vol. 4756. Berlin Heidelberg: Springer pp. 331-339., (10.1007/978-3-540-76725-1_35)

2007

• Wu, J., Smith, W. A. and Hancock, E. R. 2007. Gender classification using shape from shading. Presented at: BMVC 2007, Warwick, UK, 10-13 September 2007 Presented at Rajpoot, N. M. and Bhalerao, M. L. eds.Proceedings of the British Machine Conference. BMVA Press pp. 50.1-50.10., (10.5244/C.21.50)
• Dickens, M. P., Smith, W. A. P., Wu, J. and Hancock, E. R. . 2007. Face recognition using principal geodesic analysis and manifold learning. Presented at: Third Iberian Conference, IbPRIA 2007, Girona, Spain, 6-8 June 2007 Presented at Martí, J. ed.Pattern Recognition and Image Analysis: Third Iberian Conference, IbPRIA 2007, Girona, Spain, June 6-8, 2007, Proceedings, Part I, Vol. 4477. Lecture Notes in Computer Science Vol. 4477. Berlin Heidelberg: Springer pp. 426-434., (10.1007/978-3-540-72847-4_55)
• Wu, J., Smith, W. A. P. and Hancock, E. R. 2007. Learning mixture models for gender classification based on facial surface normals. Presented at: Third Iberian Conference, IbPRIA 2007, Girona, Spain, 6-8 June 2007 Presented at Marti, J. et al. eds.Pattern Recognition and Image Analysis: Third Iberian Conference, IbPRIA 2007, Girona, Spain, June 6-8, 2007, Proceedings, Part I, Vol. 4477. Lecture Notes in Computer Science Vol. 4477. Springer Berlin Heidelberg pp. 39-46., (10.1007/978-3-540-72847-4_7)

2006

• Wu, J., Smith, W. A. P. and Hancock, E. 2006. Gender classification using principal geodesic analysis and gaussian mixture models. Lecture Notes in Computer Science 4225, pp. 58-67. (10.1007/11892755_6)