Wenyang Liu

news

Oct 08, 2026
Our paper on industrial robotic perception received Excellent Paper recognition at an internal technical conference and led to a patent application. We have been invited to demonstrate the system at E-Forest Tech Day 2026, October 19–21, at Hyundai Uiwang R&D Center, South Korea.
Jul 10, 2026
Our paper “DriftAD: Visually-Guided Text Drift for Few-Shot Industrial Anomaly Detection” has been accepted at ACM International Conference on Multimedia (ACM MM 2026). Joint work with Tianyi Liu, Dongshuo Zhang, Kejun Wu, and Adams Wai-Kin Kong.
Apr 29, 2026
One paper has been accepted at Information Fusion.
Dec 01, 2025
One paper has been accepted at Pattern Recognition.
Nov 30, 2025
Graduated with a Ph.D. in Electrical and Electronic Engineering from Nanyang Technological University.

research projects

Industrial Robotic Perception

Nov 2025 – Present Hyundai–NTU–A*STAR

Develop foundation-model-based anomaly detection, open-vocabulary perception and 6D pose estimation. Validated a grasping pipeline on industrial parts through on-site robot demonstrations.

ACM MM

Human–Robot Collaboration

Jun 2025 – Nov 2025 Schaeffler–NTU

Evaluated 3D human pose estimation from RGB and depth data. Developed motion retargeting methods to transfer human movements to robots for human–robot collaboration.

Image Watermarking & Security

Dec 2024 – Jun 2025 Funded by DSO National Laboratories

Developed robust image watermarking and self-supervised watermark removal without paired clean images. Evaluated performance under JPEG compression, noise and resizing.

JVCIR

Open-Vocabulary Industrial Vision

Mar 2024 – Dec 2024 Schaeffler–NTU

Developed open-vocabulary detection and segmentation for recognizing objects beyond fixed categories. Studied human–object interaction recognition with limited supervision.

EMNLPACM MMKBS

Image and Video Restoration

Jan 2021 – Mar 2024 Funded by National Research Foundation

Developed methods to recover images and videos from damaged storage. Built lightweight super-resolution models and byte–image representations for identifying file fragments without metadata.

CVPRNeurIPSIEEE TMM

Efficient Video & AI Computing

Sep 2017 – Jul 2020 Chongqing University

Parallelized H.264 decoding for faster, lower-power video processing. Contributed to photonic accelerators for deep learning inference.

ICPADSDATE

selected publications

DriftAD: Visually-Guided Text Drift for Few-Shot Industrial Anomaly Detection

Wenyang Liu, Tianyi Liu, Dongshuo Zhang,

Proceedings of the ACM International Conference on Multimedia, 2026
ACM MM
CCF A

Abs Bib

We propose DriftAD, a visually-guided CLIP adaptation framework that adapts text representations to local visual context for few-shot industrial anomaly detection, achieving state-of-the-art results across 1-, 2-, and 4-shot settings with up to 1.5-point gains in AUROC and PRO.
@inproceedings{liu2026driftad, url = {https://arxiv.org/abs/2608.23723}, title = {{DriftAD}: Visually-Guided Text Drift for Few-Shot Industrial Anomaly Detection}, author = {Liu, Wenyang and Liu, Tianyi and Zhang, Dongshuo and Wu, Kejun and Kong, Wai Kin (Adams)}, booktitle = {Proceedings of the ACM International Conference on Multimedia}, year = {2026} }
PromptSR: Cascade Prompting for Lightweight Image Super-Resolution

Wenyang Liu, Chen Cai, Jianjun Gao,

IEEE Transactions on Multimedia, 2026
IEEE TMM
CCF A CAS Q1 Top JCR Q1

Abs Bib

We propose PromptSR, a cascade prompting framework for lightweight image super-resolution that leverages prompt-guided restoration to achieve efficient real-world image quality improvement.
@article{liu2026promptsr, url = {https://arxiv.org/abs/2507.04118}, title = {{PromptSR}: Cascade Prompting for Lightweight Image Super-Resolution}, author = {Liu, Wenyang and Cai, Chen and Gao, Jianjun and Wu, Kejun and Wang, Yi and Yap, Kim-Hui and Chau, Lap-Pui}, journal = {IEEE Transactions on Multimedia}, year = {2026}, publisher = {IEEE} }

SSH-Net: A Self-Supervised and Hybrid Network for Noisy Image Watermark Removal

Wenyang Liu, Jianjun Gao and Kim-Hui Yap

Journal of Visual Communication and Image Representation, 2025

JVCIR

CCF C CAS Q3 JCR Q2

Abs Bib

@article{liu2025ssh,
  url = {https://arxiv.org/abs/2505.05088},
  title = {{SSH-Net}: A Self-Supervised and Hybrid Network for Noisy Image Watermark Removal},
  author = {Liu, Wenyang and Gao, Jianjun and Yap, Kim-Hui},
  journal = {Journal of Visual Communication and Image Representation},
  pages = {104516},
  year = {2025},
  publisher = {Academic Press}
}

ByteNet: Rethinking Multimedia File Fragment Classification through Visual Perspectives

Wenyang Liu, Kejun Wu, Tianyi Liu,

IEEE Transactions on Multimedia, 2024

IEEE TMM

CCF A CAS Q1 Top JCR Q1

Abs Bib

@article{liu2024bytenet,
  url = {https://arxiv.org/abs/2410.20855},
  title = {{ByteNet}: Rethinking Multimedia File Fragment Classification through Visual Perspectives},
  author = {Liu, Wenyang and Wu, Kejun and Liu, Tianyi and Wang, Yi and Yap, Kim-Hui and Chau, Lap-Pui},
  journal = {IEEE Transactions on Multimedia},
  volume = {27},
  pages = {1305--1319},
  year = {2024},
  publisher = {IEEE}
}

Bitstream-Corrupted JPEG Images Are Restorable: Two-Stage Compensation and Alignment Framework for Image Restoration

Wenyang Liu, Yi Wang, Kim-Hui Yap,

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

CVPR

CCF A

Abs Bib

@inproceedings{liu2023bitstream_cvpr,
  url = {https://openaccess.thecvf.com/content/CVPR2023/html/Liu_Bitstream-Corrupted_JPEG_Images_Are_Restorable_Two-Stage_Compensation_and_Alignment_Framework_CVPR_2023_paper.html},
  title = {Bitstream-Corrupted {JPEG} Images Are Restorable: Two-Stage Compensation and Alignment Framework for Image Restoration},
  author = {Liu, Wenyang and Wang, Yi and Yap, Kim-Hui and Chau, Lap-Pui},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages = {9979--9988},
  year = {2023}
}

A Byte Sequence Is Worth an Image: CNN for File Fragment Classification Using Bit Shift and n-Gram Embeddings

Wenyang Liu, Yi Wang, Kejun Wu,

IEEE International Conference on Artificial Intelligence Circuits and Systems, 2023
AICAS Oral
Abs Bib

We demonstrate that byte sequences can be treated as images for file fragment classification, using bit shift and n-gram embeddings with CNN architectures.
@inproceedings{liu2023byte, url = {https://arxiv.org/abs/2304.06983}, title = {A Byte Sequence Is Worth an Image: {CNN} for File Fragment Classification Using Bit Shift and n-Gram Embeddings}, author = {Liu, Wenyang and Wang, Yi and Wu, Kejun and Yap, Kim-Hui and Chau, Lap-Pui}, booktitle = {IEEE International Conference on Artificial Intelligence Circuits and Systems}, year = {2023} }

MindReading: An Ultra-Low-Power Photonic Accelerator for EEG-Based Human Intention Recognition

Qian Lou^*, Wenyang Liu^*, Weichen Liu,

* Co-first authors

Asia and South Pacific Design Automation Conference, 2020

ASP-DAC

CCF C

Abs Bib

@inproceedings{lou2020mindreading,
  url = {https://arxiv.org/abs/2001.11954},
  title = {{MindReading}: An Ultra-Low-Power Photonic Accelerator for {EEG}-Based Human Intention Recognition},
  author = {Lou, Qian and Liu, Wenyang and Liu, Weichen and Guo, Feng and Jiang, Lei},
  booktitle = {Asia and South Pacific Design Automation Conference},
  pages = {464--469},
  year = {2020},
  organization = {IEEE}
}

HolyLight: A Nanophotonic Accelerator for Deep Learning in Data Centers

Weichen Liu, Wenyang Liu, Yichen Ye,

Second author; first author was my master’s advisor

Design, Automation & Test in Europe Conference, 2019

DATE

CCF B 140+ citations

Abs Bib

@inproceedings{liu2019holylight,
  url = {https://doi.org/10.23919/DATE.2019.8715195},
  title = {{HolyLight}: A Nanophotonic Accelerator for Deep Learning in Data Centers},
  author = {Liu, Weichen and Liu, Wenyang and Ye, Yichen and Lou, Qian and Xie, Yiyuan and Jiang, Lei},
  booktitle = {Design, Automation \& Test in Europe Conference},
  pages = {1483--1488},
  year = {2019},
  organization = {IEEE}
}