About

Yikai Wang is a postdoctoral researcher at Meta, London, working with Prof. Tao Xiang. Prior to this, he was a research fellow at MMLab@NTU, Nanyang Technological University, Singapore, working with Prof. Chen Change Loy. He received his Ph.D. in Statistics and B.Sc. in Mathematics from Fudan University, Shanghai, advised by Prof. Yanwei Fu.

His research focuses on structured generative models that infer and represent both observed and unobserved aspects of the visual world. His long-term goal is to build general-purpose generative systems that go beyond realistic simulation, enabling controllable, interactive, and physically grounded generation.

He has mentored several junior collaborators, helping guide their first research projects to publications in venues including NeurIPS, ICLR, CVPR, and ICML. He serves as an area chair and reviewer for major conferences and journals, and has co-organized several workshops and tutorials.

His research has led to several patents and proprietary models that have been acquired by companies and embedded in commercial applications.

Reach out via yi-kai.wang@outlook.com. Please let me know who you are.
My previous institutional emails from NTU and Fudan are no longer active.

News


Research

Papers

Aligned Stable Inpainting: Mitigating Unwanted Object Insertion and Preserving Color Consistency
[arxiv]
Yikai Wang*, Junqiu Yu*, Chenjie Cao, Xiangyang Xue, Yanwei Fu.
Preprint, 2026.

The Pictorial Cortex: Zero-Shot Cross-Subject fMRI-to-Image Reconstruction via Compositional Latent Modeling.
[arxiv]
Jingyang Huo, Yikai Wang, Yanwei Fu, Jianfeng Feng.
Preprint, 2026.

ActiveVLA: Injecting Active Perception into Vision-Language-Action Models for Precise 3D Robotic Manipulation.
[arxiv] [paper] [code] [data] [intro]
Zhenyang Liu, Yongchong Gu, Yikai Wang, Xiangyang Xue, Yanwei Fu.
CVPR, 2026.

Next Visual Granularity Generation.
[arxiv] [paper] [code] [intro] [简介]
Yikai Wang, Zhouxia Wang, Zhonghua Wu, Qingyi Tao, Kang Liao, Chen Change Loy.
ICLR, 2026.

Thinking with Camera: A Unified Multimodal Model for Camera-Centric Understanding and Generation.
[arxiv] [paper] [code] [intro] [简介]
Kang Liao, Size Wu, Zhonghua Wu, Linyi Jin, Chao Wang, Yikai Wang, Fei Wang, Wei Li, Chen Change Loy.
ICLR, 2026.

Spatial-Temporal Aware Visuomotor Diffusion Policy Learning.
[arxiv] [paper] [code] [intro]
Zhenyang Liu, Yikai Wang, Kuanning Wang, Longfei Liang, Xiangyang Xue, Yanwei Fu.
ICCV, 2025.

Towards Enhanced Image Inpainting: Mitigating Unwanted Object Insertion and Preserving Color Consistency.
[arxiv] [paper] [full-size PDF] [code & MISATO dataset] [intro] [demo: Youtube, Bilibili]
Yikai Wang*, Chenjie Cao*, Junqiu Yu*, Ke Fan, Xiangyang Xue, Yanwei Fu.
CVPR, 2025. (Highlight, 13.5% of accepted papers)

ReasonGrounder: LVLM-Guided Hierarchical Feature Splatting for Open-Vocabulary 3D Visual Grounding and Reasoning.
[arxiv] [paper] [code & dataset] [intro]
Zhenyang Liu, Yikai Wang, Sixiao Zheng, Tongying Pan, Longfei Liang, Yanwei Fu, Xiangyang Xue.
CVPR, 2025.

Adaptive Pruning of Pretrained Transformer via Differential Inclusions.
[arxiv] [paper] [code]
Yizhuo Ding, Ke Fan, Yikai Wang, Xinwei Sun, Yanwei Fu.
ICLR, 2025.

3D StreetUnveiler with Semantic-aware 2DGS - a simple baseline.
[arxiv] [paper] [code] [intro]
Jingwei Xu, Yikai Wang, Yiqun Zhao, Yanwei Fu, Shenghua Gao.
ICLR, 2025.

Repositioning the Subject within Image.
[arxiv] [paper] [full-size PDF] [code & ReS dataset] [intro] [demo: Youtube, Bilibili]
Yikai Wang, Chenjie Cao, Ke Fan, Qiaole Dong, Yifan Li, Xiangyang Xue, Yanwei Fu.
TMLR, 2024. (J2C Certification, 10% of accepted papers)

LEA: Learning Latent Embedding Alignment Model for fMRI Decoding and Encoding.
[arxiv] [paper] [code]
Xuelin Qian*, Yikai Wang*, Xinwei Sun, Yanwei Fu, Xiangyang Xue, Jianfeng Feng.
TMLR, 2024.

Unified Lexical Representation for Interpretable Visual-Language Alignment.
[arxiv] [paper] [code] [intro]
Yifan Li, Yikai Wang, Yanwei Fu, Dongyu Ru, Zheng Zhang, Tong He.
NeurIPS, 2024.

Towards Global Optimal Visual In-Context Learning Prompt Selection.
[arxiv] [paper] [code] [intro]
Chengming Xu*, Chen Liu*, Yikai Wang, Yuan Yao, Yanwei Fu.
NeurIPS, 2024.

NeuroPictor: Refining fMRI-to-Image Reconstruction via Multi-individual Pretraining and Multi-level Modulation.
[arxiv] [paper] [code] [intro]
Jingyang Huo*, Yikai Wang*, Yun Wang*, Xuelin Qian, Chong Li, Yanwei Fu, Jianfeng Feng.
ECCV, 2024.

LeftRefill: Filling Right Canvas based on Left Reference through Generalized Text-to-Image Diffusion Model.
[arxiv] [paper] [code] [intro]
Chenjie Cao, Yunuo Cai, Qiaole Dong, Yikai Wang, Yanwei Fu.
CVPR, 2024.

Test-Time Linear Out-of-Distribution Detection.
[paper] [code]
Ke Fan*, Tong Liu*, Xingyu Qiu, Yikai Wang, Lian Huai, Zeyu Shangguan, Shuang Gou, Fengjian Liu, Yuqian Fu, Yanwei Fu, Xingqun Jiang.
CVPR, 2024.

Coarse-to-Fine Amodal Segmentation with Shape Prior.
[arxiv] [paper] [code] [intro]
Jianxiong Gao, Xuelin Qian, Yikai Wang, Tianjun Xiao, Tong He, Zheng Zhang, Yanwei Fu.
ICCV, 2023.

Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels.
[arxiv] [paper] [code] [intro] [简介]
Yikai Wang*, Yanwei Fu*, Xinwei Sun.
TPAMI, 2023.

Scalable Penalized Regression for Noise Detection in Learning with Noisy Labels.
[arxiv] [paper] [code] [intro] [简介]
Yikai Wang, Xinwei Sun, Yanwei Fu.
CVPR, 2022.

How to Trust Unlabeled Data? Instance Credibility Inference for Few-Shot Learning.
[arxiv] [paper] [code] [intro] [简介]
Yikai Wang, Li Zhang, Yuan Yao, Yanwei Fu.
TPAMI, 2021.

Instance Credibility Inference for Few-Shot Learning.
[arxiv] [paper] [code] [intro] [简介]
Yikai Wang, Chengming Xu, Chen Liu, Li Zhang, Yanwei Fu.
CVPR, 2020.

Talks

Structured Generative Vision: From Context-Stable Inpainting to Next Visual Granularity Generation.
[slides]
Xi'an Jiaotong University, 2026.05;
Fudan University, 2026.05;
Shanghai Innovation Insitute, 2026.05.

Filling Right Canvas based on Left Reference through Generalized Text-to-Image Diffusion Model.
[slides] [Bilibili video (in Chinese, starts at 1:18:40)]
Oral presentation at Pre-CVPR@Shanghai, 2024.05.

Advancing Image Inpainting: From Versatility to Consistency.
[slides]
Nanyang Technological University, 2024.04.

Clean Sample Selection Algorithms with Statistical Sparsity Analysis.
[slides]
Technical University of Munich, 2024.03;
Institute of Science and Technology Austria, 2024.04.

Few-shot Learning by Statistical Methods.
[slides]
CVPR 2023 tutorial, 2023.06:
Few-shot Learning from Meta-Learning, Statistical Understanding to Applications.

Sparse Learning for Noisy Data Detection.
[Youtube][Bilibili][slides]
CVPR 2022 tutorial, 2022.06:
Sparse Learning in Neural Networks and Robust Statistical Analysis.

Grants and Awards

Timeline

Service

Teaching

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