About


Yikai Wang is a research fellow at the MMLab@NTU, working with Prof. Chen Change Loy, affiliated with S-Lab, Nanyang Technological University, Singapore. He obtained his Ph.D. in Statistics at Fudan University in 2024, advised by Prof. Yanwei Fu. Prior to this, He completed B.S. in Mathematics at Fudan University in 2019. His research spans statistical machine learning, computer vision, and foundation models, with a focus on content creation, multi-modality and subset selection.

Always available with yi-kai.wang@outlook.com, please let me know who you are.
My Fudan email is no longer active.

News



Research


Publications


Arranged by topic and in chronological order. Updated list can be found at Google Scholar. (*): equal contribution; (): corresponding author(s).

Content Creation

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

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.

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.

Multi-Modality

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, Xiangyang Xue, Yanwei Fu.
CVPR, 2025.

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.

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.

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.

Subset Selection

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

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.

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.

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

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

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

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

Experience


Research Fellow,
2024 - present, Nanyang Technological University, Singapore.

Education


Ph.D. in Statistics,
2019 - 2024, Fudan University.
B.S. in Mathematics,
2015 - 2019, Fudan University.

Awards


Service


Teaching


Neural Network and Deep Learning,
TA, 2019-2022 Springs, Fudan University.

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