I am Tianxing Li (李天行), a lecturer at Beijing University of Technology (北京工业大学). I received my Ph.D. in Computer Graphics in 2021 from the University of Tokyo, under the supervision of Prof. Kanai.
During my Ph.D., I have worked on using machine learning methods to realize realistic animations in real-time, especially for characters and garments. I am also intersted in the visualization and interpretability of neural netoworks.
Tianxing Li, Zhi Qiao, Zihui Li, Rui Shi, Qing Zhu. GarTrans: Transformer-Based Architecture for Dynamic and Detailed Garment Deformation. Computational Visual Media, accept.
Tianxing Li, Rui Shi, Qing Zhu, Takashi Kanai. SwinGar: Spectrum-Inspired Neural Dynamic Deformation for Free-Swinging Garments. IEEE Transactions on Visualization and Computer Graphics, 30(10), pp.6913-6927, 2024. (presented at Pacific Graphics 2024)
Tianxing Li, Rui Shi, Zihui Li, Takashi Kanai, Qing Zhu. Efficient deformation learning of varied garments with a structure-preserving multilevel framework. ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, 2024.
Rui Shi, Tianxing Li, Liguo Zhang, Yasushi Yamaguchi. Visualization Comparison of Vision Transformers and Convolutional Neural Networks. IEEE Transactions on Multimedia, 2024, 26: 2327-2339.
Tianxing Li, Rui Shi, Takashi Kanai. Detail-Aware Deep Clothing Animations Infused with Multi-Source Attributes. Computer Graphics Forum, 42(1), pp.231-244, 2023. (presented at Eurographics 2023)
Rui Shi, Tianxing Li, Yasushi Yamaguchi. Understanding Contributing Neurons via Attribution Visualization. Neurocomputing, 550:126492, 2023.
Zhi Qiao, Tianxing Li, Li Hui, Ruijun Liu. A Deep Learning‐Based Framework for Fast Generation of Photorealistic Hair Animations. IET Image Processing, 17(2), pp.375-387, 2023.
Rui Shi, Tianxing Li, Yasushi Yamaguchi. Region-Conscious Visualization of Output-Targeted Neuron Features. Visual Computing, Article No. 40, 2022.
Rui Shi, Tianxing Li, Yasushi Yamaguchi. Output-Targeted Baseline for Neuron Attribution Calculation. Image and Vision Computing, 124: 104516, 2022.
Zhen Luo, Tianxing Li, Takashi Kanai. GarMatNet: A Learning-based Method for Predicting 3D Garment Mesh with Parameterized Materials. 14th ACM SIGGRAPH Conference on Motion, Interaction, and Games (MIG 2021), Article No.4, pp.1-10, 2021.
Tianxing Li, Rui Shi, Takashi Kanai. MultiResGNet: Approximating Nonlinear Deformation via Multi-Resolution Graphs. Computer Graphics Forum, 40(2) (Eurographics 2021 Conference Issue), pp.537-548, 2021.
Tianxing Li, Rui Shi, Takashi Kanai. DenseGATs: A Graph-Attention-Based Network for Nonlinear Character Deformation. ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games (San Francisco, CA, 15-17 September 2020), Article No.5, May 2020.
Rui Shi, Tianxing Li, Yasushi Yamaguchi. Class-Discriminative Feature Group and its Visualization. Visual Computing, 2020, Article No.36.
Rui Shi1, Tianxing Li1, Yasushi Yamaguchi. Group Visualization of Class-Discriminative Features. Neural Networks, 2020, 129: 75-90.
Rui Shi, Tianxing Li, Yasushi Yamaguchi. An Attribution-Based Pruning Method for Real-Time Mango Detection with YOLO Network. Computers and Electronics in Agriculture, 2020, 169: 105214.
Tianxing Li, Rui Shi, Takashi Kanai. MultiResGNet: Approximating Nonlinear Deformation via Multi-Resolution Graphs. Visual Computing 2021, Invited presentation.
Tianxing Li, Automatic Deformation Refinement for Animated Characters via Deep Graph Networks. Invited presentation at Huawei Technologies Japan K.K.
Tianxing Li, Rui Shi, Takashi Kanai. DenseGATs: キャラクタの非線形変形のためのグラフアテンションネットワーク. Visual Computing 2020 ポスター, P41, オンライン, 12月, 2020.
Rui Shi, Tianxing Li, Yasushi Yamaguchi. An Attribution-Based Pruning Method for Single Object Detection Network. Technical Committee on Pattern Recognition and Media Understanding (PRMU), 2019, 119 (10): 17-20.