Minghui Hu


Currently, I am a Ph.D Candidate at Nanyang Technological University in Singapore, advised by Prof. P. N. Suganthan. Previousely, I received my MSc. degree in Electric and Electrical Engineering from NTU in 2019. Parallel to my doctoral studies, I hold a position as a researcher at Temasek Lab @ NTU, under the supervision of Dr. Sirajudeen s/o Gulam Razul.

I've had the distinct privilege of collaborating with Prof. T.J.Cham and Prof. Dacheng Tao from NTU,  Dr. Chuanxia Zheng from VGG, University of Oxford and Dr. Chaoyue Wang from University of Sydney. I also had memorable experiences as a research intern Sensetime Research, JD Explore Academy and MiniMax.

Email  /  Google Scholar  /  Github  /  LinkedIn

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My research focuses on generative models, multi-modality learning, and its applications in many domains, particularly 2D Image Generation. Prior to this, I was working on a network model with a simple topology named randomized neural networks.

Trajectory Consistency Distillation
Jianbin Zheng *, Minghui Hu *, Zhongyi Fan, Chaoyue Wang, Changxing Ding, Dacheng Tao, Tat-Jen Cham
arxiv, 2024  
project page / arXiv / code / HF Model / HF Space

We distill a consistency model based on diffusion trajectory to improve the sample quality.

* equal contribution

One More Step: A Versatile Plug-and-Play Module for Rectifying Diffusion Schedule Flaws and Enhancing Low-Frequency Controls
Minghui Hu, Jianbin Zheng, Chuanxia Zheng, Chaoyue Wang, Dacheng Tao, Tat-Jen Cham
CVPR, 2024  
project page / arXiv / code / HF Model / HF Space

We develop a versatile plug-and-play module to fix the scheduler flaws for diffusion models.

Cocktail🍸: Mixing Multi-Modality Controls for Text-Conditional Image Generation
Minghui Hu, Jianbin Zheng, Daqing Liu, Chuanxia Zheng, Chaoyue Wang, Dacheng Tao, Tat-Jen Cham
NeurIPS, 2023  
project page / arXiv / code / HF Model

We develop a generalized HypreNetwork for multi-modality control based on text-to-image generative model.

Self-Distillation for Randomized Neural Networks
Minghui Hu, Ruobin Gao, P.N.Suganthan,
IEEE / Code

We integrate self-distillation into the randomized neural network to improve the generalization performance.

MMoT: Mixture-of-Modality-Tokens Transformer for Composed Multimodal Conditional Image Synthesis
Jianbin Zheng, Daqing Liu, Chaoyue Wang, Minghui Hu, Zuopeng Yang, Changxing Ding, Dacheng Tao,
project page / arXiv

We introduce a Mixture-of-Modality-Tokens Transformer (MMoT) that adaptively fuses fine-grained multimodal control signals for multi-modality image generation.

Versatile LiDAR-Inertial Odometry with SE(2) Constraints for Ground Vehicles
Jiayang Chen, Han Wang, Minghui Hu, P.N.Suganthan,
RA-L & IROS, 2023  

We propose a hybrid LiDAR-inertial SLAM framework that leverages both the on-board perception system and prior information such as motion dynamics to improve localization performance.

Class-Incremental Learning on Multivariate Time Series Via Shape-Aligned Temporal Distillation
Zhongzheng Qiao, Minghui Hu, Xudong Jiang, P.N.Suganthan, Ramasamy Savitha,
ICASSP, 2023  

We propose to exploit Soft-Dynamic Time Warping (Soft-DTW) for knowledge distillation, which aligns the feature maps along the temporal dimension before calculating the discrepancy.

Unified Discrete Diffusion for Simultaneous Vision-Language Generation
Minghui Hu, Chuanxia Zheng, Zuopeng Yang, Tat-Jen Cham, Chaoyue Wang, Zuopeng Yang, Dacheng Tao, P.N.Suganthan
ICLR, 2023  
project page / arXiv / PDF

We construct a unified discrete diffusion model for simultaneous vision-language generation.

Representation Learning Using Deep Random Vector Functional Link Networks for Clustering
Minghui Hu, P.N.Suganthan

We use manifold regularisation to learn the representation from the randomised networks.

Global Context with Discrete Diffusion in Vector Quantised Modelling for Image Generation
Minghui Hu, Yujie Wang, Tat-Jen Cham, Jianfei Yang, P.N.Suganthan
CVPR, 2022  
arXiv / PDF

Instead of AutoRegresive Transformers, we use Discrete Diffusion Model to obtain a better global context for image generation.

Academic Services

Conference Program Committee Member

CVPR    2022 - 2024
ICCV    2023
ECCV    2024
ACM MM    2024
NeurIPS    2023
ICLR    2023, 2024
ICASSP    2023, 2024
IJCNN    2020 - 2024

Journal Reviewer

T-NNLS, T-Cyb, PR, NeuNet, Neucom, ASOC, EAAI, IJCV

Yep it's another Jon Barron website.
Last updated Sep. 2023.