Dr Jing Wu

2026

• Lakhani, T. et al., 2026. Methodologies for diffusion model interpretability: A systematic review. IEEE Transactions on Artificial Intelligence 7 (7), pp.3653-3670. (10.1109/TAI.2025.3648376)

2025

• Gao, Y. et al. 2025. Deep reinforcement learning for localisability-aware mapless navigation. IET Cyber-Systems and Robotics 7 (1) e70018. (10.1049/csy2.70018)
• Huo, J. et al., 2025. REST: A resolution preserving metwork for photorealistic style transfer via semantic distillation. Computer Vision and Image Understanding 262 104544. (10.1016/j.cviu.2025.104544)
• Li, Z. et al., 2025. RuleExplorer: A scalable matrix visualization for understanding tree ensemble classifiers. IEEE Transactions on Visualization and Computer Graphics 31 (9), pp.6370-6384. (10.1109/TVCG.2024.3514115)
• Alsudays, N. et al. 2025. Multi-class part parsing based on multi-class boundaries. Presented at: IEEE International Conference on Image Processing Anchorage, AK, USA 14-17 September 2025. 2025 IEEE International Conference on Image Processing (ICIP). IEEE. , pp.2498-2503. (10.1109/icip55913.2025.11084502)
• Huo, J. et al., 2025. Dictionary based generative adversarial network for multi-collection style transfer. IEEE Transactions on Multimedia (10.1109/TMM.2025.3599024)
• Xu, M. et al. 2025. RGB-D video mirror detection. Presented at: WACV 2025 Tucson, Arizona 28 February - 04 March 2025. 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE. , pp.9640-9649. (10.1109/WACV61041.2025.00933)

2024

• Gao, Y. et al. 2024. Mapless navigation via Hierarchical Reinforcement Learning with memory-decaying novelty. Robotics and Autonomous Systems 182 104815. (10.1016/j.robot.2024.104815)
• Gao, Y. et al. 2024. Efficient hierarchical reinforcement learning for mapless navigation with predictive neighbouring space scoring. IEEE Transactions on Automation Science and Engineering 21 (4), pp.5457-5472. (10.1109/TASE.2023.3312237)
• Njuod, A. et al. 2024. GRPSNET: Multi-class part parsing based on graph reasoning. Presented at: IEEE Conference on Multimedia Expo 2024 Niagara Falls, Canada 15-19 July 2024. IEEE International Conference on Multimedia and Expo (ICME). IEEE. , pp.1-10. (10.1109/ICME57554.2024.10687831)
• Wu, J. et al. 2024. Fusion of short-term and long-term attention for video mirror detection. Presented at: IEEE Conference on Multimedia Expo 2024 Niagara Falls, Canada 15-19 July 2024. 2024 IEEE International Conference on Multimedia and Expo (ICME). IEEE. , pp.1-9. (10.1109/icme57554.2024.10688367)
• Liang, Y. et al. 2024. Efficient precision and recall metrics for assessing generative models using hubness-aware sampling. Presented at: The Forty-first International Conference on Machine Learning (ICML) Vienna, Austria 21-27 July 2024. Vol. 235., pp.29682-29699.
• Huo, J. et al., 2024. Towards efficient image and video style transfer via distillation and learnable feature transformation. Computer Vision and Image Understanding 241 103947. (10.1016/j.cviu.2024.103947)
• Yang, X. et al. 2024. GAM: General Affordance-based Manipulation for contact-rich object disentangling tasks. Neurocomputing 578 127386. (10.1016/j.neucom.2024.127386)
• Sun, J. et al. 2024. RSMPNet: Relationship guided semantic map prediction. Presented at: IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Hawaii, USA 4-8 January 2024. Proceedings of the 2024 IEEE/CVF Winter Conference on Applications of Computer Vision. IEEE. , pp.302-311. (10.1109/WACV57701.2024.00037)
• Wang, T. et al. 2024. Sparse convolutional networks for surface reconstruction from noisy point clouds. Presented at: IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Hawaii, USA 4-8 January 2024. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. IEEE. , pp.3200-3209. (10.1109/WACV57701.2024.00318)
• Yang, W. et al., 2024. Interactive reweighting for mitigating label quality issues. IEEE Transactions on Visualization and Computer Graphics 30 (3), pp.1837-1852. (10.1109/TVCG.2023.3345340)
• Zappalá, S. et al. 2024. In vivo strain measurements in the human buttock during sitting using MR-based digital volume correlation. Journal of Biomechanics 163 111913. (10.1016/j.jbiomech.2023.111913)
• Gao, Y. et al., 2024. Object goal navigation based on path planning characteristics. CAAI Transactions on Intelligence Technology 19 , pp.217-227. (10.11992/tis.202309001)
• Herbert, P. et al. 2024. Benchmarking visual SLAM methods in mirror environments. Computational Visual Media 10 (2), pp.215-241. (10.1007/s41095-022-0329-x)
• Sun, J. et al. 2024. A survey of object goal navigation. IEEE Transactions on Automation Science and Engineering 22 , pp.2292-2308. (10.1109/TASE.2024.3378010)

2023

• Chen, C. et al., 2023. A unified interactive model evaluation for classification, object detection, and instance segmentation in computer vision. Presented at: IEEE VIS 2023 Melbourne, Australia 22-27 October 2023. Institute of Electrical and Electronics Engineers. , pp.76-86. (10.1109/TVCG.2023.3326588)
• Yang, X. et al. 2023. Recent advances of deep robotic affordance learning: a reinforcement learning perspective. IEEE Transactions on Cognitive and Developmental Systems 15 (3), pp.1139-1149. (10.1109/TCDS.2023.3277288)
• Song, S. et al. 2023. Feature proliferation — the "cancer" in StyleGAN and its treatments. Presented at: International Conference on Computer Vision (ICCV) 2023 Paris, France October 1 - 6, 2023. Proceedings of IEEE/CVF International Conference on Computer Vision. IEEE. , pp.2360-2370. (10.1109/ICCV51070.2023.00224)
• Gao, Y. et al. 2023. Hierarchical reinforcement learning-based mapless navigation with predictive exploration worthiness. Presented at: IEEE International Conference on Mechatronics and Automation Harbin, Heilongjiang, China 6-9 August 2023. Proceedings of the 2023 IEEE International Conference on Mechatronics and Automation. IEEE. , pp.636-643. (10.1109/ICMA57826.2023.10215569)
• Alsudays, N. et al. 2023. Afpsnet: multi-class part parsing based on scaled attention and feature fusion. Presented at: IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Waikoloa, Hawaii, 3-7 Jan 2023. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE. , pp.4022-4031. (10.1109/WACV56688.2023.00402)
• Xia, J. et al., 2023. Interactive visual cluster analysis by contrastive dimensionality reduction. IEEE Transactions on Visualization and Computer Graphics 29 (1), pp.734-744. (10.1109/TVCG.2022.3209423)
• Wang, T. et al. 2023. RPS-Net: Indoor scene point cloud completion using RBF-point sparse convolution. Presented at: EG UK Computer Graphics & Visual Computing Aberystwyth, UK 14-15 September 2023. Proceedings EG UK Computer Graphics & Visual Computing. Eurographics - The European Association for Computer Graphics. (10.2312/cgvc.20231188)

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. et al. 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. et al., 2022. Playing lottery tickets in style transfer models. Presented at: MM '22: The 30th ACM International Conference on Multimedia 10-14 October 2022. M4MM '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. et al. 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) Bristol, United Kingdom 1-3 September 2022. 2022 27th International Conference on Automation and Computing (ICAC). IEEE. (10.1109/ICAC55051.2022.9911100)
• Yang, X. et al. 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)
• Chen, C. et al., 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. et al., 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 2021. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE. , pp.3081-3090. (10.1109/ICCV48922.2021.00309)
• Liang, Y. et al. 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.ML Research Press. , pp.13271-13284.

2021

• Huo, J. et al., 2021. Manifold alignment for semantically aligned style transfer. Presented at: CVF/IEEE International Conference on Computer Vision (ICCV 2021) Virtual / Montreal, QC, Canada 11-17 October 2021. Proceedings of the IEEE/CVF International Conference on Computer Vision. IEEE. , pp.14841-14849. (10.1109/ICCV48922.2021.01459)
• Xie, Q. et al., 2021. VENet: Voting Enhancement Network for 3D object detection. Presented at: CVF/IEEE International Conference on Computer Vision (ICCV 2021) Virtual / Montreal, QC, Canada 11-17 October 2021. Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision. IEEE. , pp.3692-3701. (10.1109/ICCV48922.2021.00369)
• Yang, X. et al. 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. Published in: Fox, C. et al., Towards Autonomous Robotic Systems. TAROS 2021. Lecture Notes in Computer Science Springer. , pp.14-24. (10.1007/978-3-030-89177-0_2)
• Hou, H. et al., 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) 17684. (10.1038/s41598-021-97150-5)
• Chen, C. et al., 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)
• Cao, K. et al., 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. et al., 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. et al., 2021. Learning 3D face reconstruction from a single sketch. Graphical Models 115 101102. (10.1016/j.gmod.2021.101102)

2020

• Xie, Q. et al., 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 2020. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE. , pp.10444-10453. (10.1109/CVPR42600.2020.01046)

2019

• Pan, Y. et al., 2019. InSocialNet: Interactive visual analytics for role-event videos. Computational Visual Media 5 (4), pp.375-390. (10.1007/s41095-019-0157-9)
• Xiang, S. et al., 2019. Interactive correction of mislabeled training data. Presented at: IEEE VIS 2019 Vancouver, BC, Canada 20-25 October 2019. 2019 IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE(10.1109/VAST47406.2019.8986943)
• Wang, X. et al., 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. et al., 2019. Computer-assisted relief modelling: a comprehensive survey. Presented at: Eurographics Conference 2019 STARs Genova, Italy 6-10 May 2019. Vol. 38.Vol. 2. Wiley-Blackwell. , pp.521-534. (10.1111/cgf.13655)

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. et al., 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. et al. 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. et al. 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. Published in: Gimel'farb, G. et al., 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

• 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)
• 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)
• 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 2011. 2011 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. Published in: 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. et al. 2009. Extracting gender discriminating features from facial needle-maps. Presented at: 2009 IEEE International Conference on Image Processing (ICIP) Cairo, Egypt 7-10 Nov 2009. 2009 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. 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. Published in: 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. 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. Published in: da Vitoria Lobo, N. et al., 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. 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. Published in: 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)
• 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 2008. 19th 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 2008. 19th 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)

2007

• Dickens, M. P. et al., 2007. Face recognition using principal geodesic analysis and manifold learning. Presented at: Third Iberian Conference, IbPRIA 2007 Girona, Spain 6-8 June 2007. Published in: 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. and Hancock, E. R. 2007. Gender classification using shape from shading. Presented at: BMVC 2007 Warwick, UK 10-13 September 2007. Published in: 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)
• 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. Published in: Marti, J. et al., 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)