Learning a Hierarchical Latent-Variable Model of Voxelized 3D Shapes. - Shikun Liu; Alexander G. Ororbia II; C. Lee Giles (CoRR, 2017)

Learning a Hierarchical Latent-Variable Model of 3D Shapes. - Shikun Liu; C. Lee Giles; Alexander Ororbia (3DV, 2018)

Research on barker coded excitation method for magneto-acoustic imaging. - Shunqi Zhang; Xiaoqing Zhou; Shikun Liu; Tao Yin; Zhipeng Liu 003 (Biomed. Signal Process. Control., 2018)

End-To-End Multi-Task Learning With Attention. - Shikun Liu; Edward Johns; Andrew J. Davison (CVPR, 2019)

Self-Supervised Generalisation with Meta Auxiliary Learning. - Shikun Liu; Andrew J. Davison; Edward Johns (NeurIPS, 2019)

Shape Adaptor: A Learnable Resizing Module. - Shikun Liu; Zhe Lin 001; Yilin Wang 002; Jianming Zhang 001; Federico Perazzi; Edward Johns (ECCV (12), 2020)

iMAP: Implicit Mapping and Positioning in Real-Time. - Edgar Sucar; Shikun Liu; Joseph Ortiz; Andrew J. Davison (ICCV, 2021)

Media audio-visual program supervision system based on network topology. - Zhongfu Li; Shikun Liu (Int. J. Syst. Assur. Eng. Manag., 2021)

Bootstrapping Semantic Segmentation with Regional Contrast. - Shikun Liu; Shuaifeng Zhi; Edward Johns; Andrew J. Davison (ICLR, 2022)

AST-Net: Lightweight Hybrid Transformer for Multimodal Brain Tumor Segmentation. - Peixu Wang; Shikun Liu; Jialin Peng (ICPR, 2022)

Auto-Lambda: Disentangling Dynamic Task Relationships. - Shikun Liu; Stephen James; Andrew J. Davison; Edward Johns (Trans. Mach. Learn. Res., 2022)

vMAP: Vectorised Object Mapping for Neural Field SLAM. - Xin Kong; Shikun Liu; Marwan Taher; Andrew J. Davison (CVPR, 2023)

Structural Re-weighting Improves Graph Domain Adaptation. - Shikun Liu; Tianchun Li; Yongbin Feng; Nhan Tran; Han Zhao 002; Qiang Qiu; Pan Li 005 (ICML, 2023)

Prismer: A Vision-Language Model with An Ensemble of Experts. - Shikun Liu; Linxi Fan; Edward Johns; Zhiding Yu; Chaowei Xiao; Anima Anandkumar (CoRR, 2023)

GDL-DS: A Benchmark for Geometric Deep Learning under Distribution Shifts. - Deyu Zou; Shikun Liu; Siqi Miao 001; Victor Fung; Shiyu Chang; Pan Li 005 (CoRR, 2023)

EscherNet: A Generative Model for Scalable View Synthesis. - Xin Kong; Shikun Liu; Xiaoyang Lyu; Marwan Taher; Xiaojuan Qi 001; Andrew J. Davison (CVPR, 2024)

Pairwise Alignment Improves Graph Domain Adaptation. - Shikun Liu; Deyu Zou; Han Zhao 002; Pan Li 005 (ICML, 2024)

GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts. - Deyu Zou; Shikun Liu; Siqi Miao 001; Victor Fung; Shiyu Chang; Pan Li 005 (NeurIPS, 2024)

MarDini: Masked Autoregressive Diffusion for Video Generation at Scale. - Haozhe Liu; Shikun Liu; Zijian Zhou; Mengmeng Xu; Yanping Xie; Xiao Han; Juan C. Pérez; Ding Liu; Kumara Kahatapitiya; Menglin Jia; Jui-Chieh Wu; Sen He 001; et al. (CoRR, 2024)

Prismer: A Vision-Language Model with Multi-Task Experts. - Shikun Liu; Linxi Fan; Edward Johns; Zhiding Yu; Chaowei Xiao; Anima Anandkumar (Trans. Mach. Learn. Res., 2024)

Learning Flow Fields in Attention for Controllable Person Image Generation. - Zijian Zhou; Shikun Liu; Xiao Han; Haozhe Liu; Kam Woh Ng; Tian Xie 003; Yuren Cong; Hang Li; Mengmeng Xu; Juan-Manuel Pérez-Rúa; Aditya Patel; Tao Xiang 002; et al. (CVPR, 2025)

MarDini: Masked Auto-regressive Diffusion for Video Generation at Scale. - Haozhe Liu; Shikun Liu; Zijian Zhou; Mengmeng Xu; Yanping Xie; Xiao Han; Juan Camilo Pérez; Ding Liu; Kumara Kahatapitiya; Menglin Jia; Jui-Chieh Wu; Sen He 001; et al. (Trans. Mach. Learn. Res., 2025)

Model Generalization on Text Attribute Graphs: Principles with Large Language Models. - Haoyu Wang 004; Shikun Liu; Rongzhe Wei; Pan Li 005 (CoRR, 2025)

Structural Alignment Improves Graph Test-Time Adaptation. - Hans Hao-Hsun Hsu; Shikun Liu; Han Zhao; Pan Li (CoRR, 2025)

Graph-KV: Breaking Sequence via Injecting Structural Biases into Large Language Models. - Haoyu Wang 004; Peihao Wang; Mufei Li; Shikun Liu; Siqi Miao 001; Zhangyang Wang; Pan Li 005 (CoRR, 2025)