Projects

Here presents some representative projects which I have worked on. My selected publications are listed at the bottom of this page. The most up-to-date publication list can be found in my Google Scholar.

If you like my design and would like to use it in your research, please check out Clarity template.

Kaleido NEW

Scaling Sequence-to-Sequence Generative Neural Rendering

EscherNet

A Generative Model for Scalable View Synthesis

Prismer

A Vision-Language Model with Multi-Task Vision Experts

Auto-Lambda

A Unified Optimisation Framework for Multi-Task and Auxiliary Learning

ReCo

Bootstrapping Semantic Segmentation with Pixel-Level Contrastive Learning

Shape Adaptor

Learning Architecture-Agnostic Stride Patterns for Convolutional Neural Networks

MAXL

Self-Supervised Generalisation with Meta Auxiliary Learning

MTAN

Multi-Task Learning with Feature-Level Attention

VSL

A Hierarchical Latent-Variable Model for 3D Shape Generation

Selected Publications


ICML 2026

Rays as Pixels: Learning A Joint Distribution of Videos and Camera Trajectories [Paper] [Blog]

Wonbong Jang, Shikun Liu, Soubhik Sanyal, Juan C. Pérez, Kam Woh Ng, Sanskar Agrawal, Juan-Manuel Pérez-Rúa, Yiannis Douratsos, and Tao Xiang


CVPR 2026

Scaling Zero-Shot Reference-to-Video Generation [Paper] [Blog]

Zijian Zhou, Shikun Liu, Haozhe Liu, Haonan Qiu, Zhaochong An, Weiming Ren, Zhiheng Liu, Xiaoke Huang, Kam Woh Ng, Tian Xie, Xiao Han, Yuren Cong, Hang Li, Chuyan Zhu, Aditya Patel, Tao Xiang, and Sen He


ICLR 2026

Scaling Sequence-to-Sequence Generative Neural Rendering [Paper] [Blog]

Shikun Liu, Kam Woh Ng, Wonbong Jang, Jiadong Guo, Junlin Han, Haozhe Liu, Yiannis Douratsos, Juan C. Pérez, Zijian Zhou, Chi Phung, Tao Xiang, and Juan-Manuel Pérez-Rúa


TMLR 2025

MarDini: Masked Autoregressive Diffusion for Video Generation at Scale [Paper] [Blog]

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, Tao Xiang, Jürgen Schmidhuber, Juan-Manuel Pérez-Rúa


CVPR 2024

EscherNet: A Generative Model for Scalable View Synthesis [Paper] [Blog] [Code]

Xin Kong, Shikun Liu, Xiaoyang Lyu, Marwan Taher, Xiaojuan Qi, and Andrew J. Davison


TMLR 2024

Prismer: A Vision-Language Model with Multi-Task Experts [Paper] [Blog] [Code] [Demo]

Shikun Liu, Linxi Fan, Edward Johns, Zhiding Yu, Chaowei Xiao, and Anima Anandkumar


CVPR 2023

vMAP: Vectorised Object Mapping for Neural Field SLAM [Paper] [Blog] [Code]

Xin Kong, Shikun Liu, Marwan Taher, and Andrew J. Davison


TMLR 2022

Auto-Lambda: Disentangling Dynamic Task Relationships [Paper] [Blog] [Code] [Slides]

Shikun Liu, Stephen James, Andrew J. Davison, and Edward Johns


ICLR 2022

Bootstrapping Semantic Segmentation with Regional Contrast [Paper] [Blog] [Code] [Slides]

Shikun Liu, Shuaifeng Zhi, Edward Johns, and Andrew J. Davison


ICCV 2021

iMAP: Implicit Mapping and Positioning in Real-Time [Paper] [Blog] [Code] [Video]

Edgar Sucar, Shikun Liu, Joseph Ortiz, and Andrew J. Davison


ECCV 2020

Shape Adaptor: A Learnable Resizing Module [Paper] [Blog] [Code] [Slides]

Shikun Liu, Zhe Lin, Yilin Wang, Jianming Zhang, Federico Perazzi, and Edward Johns


NeurIPS 2019

Self-Supervised Generalisation with Meta Auxiliary Learning [Paper] [Blog] [Code] [Slides]

Shikun Liu, Andrew J. Davison, and Edward Johns


CVPR 2019

End-to-End Multi-Task Learning with Attention [Paper] [Blog] [Code]

Shikun Liu, Edward Johns, and Andrew J. Davison


3DV 2018

Learning a Hierarchical Latent-Variable Model of 3D Shapes [Paper] [Blog] [Code]

Shikun Liu, C. Lee Giles, and Alexander G. Ororbia II.