Huan Wang

Welcome to my webpage!👋🏻 My name is Huan Wang (Chinese: 王欢. My first name means "happiness or joy" in Chinese). I am now a final-year Ph.D. candidate at SMILE Lab, Northeastern University (Boston, USA), advised by Prof. Yun (Raymond) Fu. Before that, I earned my M.S. (2019) and B.E. (2016) degrees from Zhejiang University (Hangzhou, China), advised by Prof. Haoji Hu. I also visited VLLab at University of California, Merced, luckily working with Prof. Ming-Hsuan Yang. I have been actively collaborating with fatanstic industrial researchers from Google / Snap / MERL / Meta / Alibaba, etc.

My research orbits Efficient Deep Learning (a.k.a. Model Compression), spanning image classifcation / detection / segmentation tasks [GReg, Pruning-at-Initialization Survey, TPP] to neural style transfer [Collaborative-Distillation], single image super-resolution [ASSL/GASSL, SRP, ISS-P], 3D novel view synthesis / neural rendering / NeRF / NeLF [R2L, MobileR2L], and text-to-image generation / diffusion models / Stable Diffusion [SnapFusion].

I do my best towards easily reproducible research.

My email: wang.huan [at] northeastern [dot] edu.

[ Google Scholar ]   [ GitHub ]   [ LinkedIn ]   [ Twitter ]

profile photo
Openings / Collaborations
  • Ph.D./M.S./Visiting Students: Prof. Yu Yin from our lab joined the Department of Computer and Data Science at Case Western Reserve University (CWRU) as a Tenure-Track AP in Fall 2023. She is recruiting new Ph.D./M.S./visiting students, working on generative AI problems. Welcome to contact her if you are interested!
  • I am open to collaborations (undergrad and junior grad students are particularly welcome) on topics in efficient deep learning, GenAI, digital human, etc. Feel free to reach out if you are interested!
Recent News
  • 2024/01 [ICLR'24] One paper proposing a simple and effective data augmentation method for improved action recognition is accepted by ICLR'24. Congrats to Yitian!
  • 2023/11 [Award] Received Northeastern PhD Network Travel Award. Thanks to Northeastern!
  • 2023/10 [Award] Received NeurIPS'23 Scholar Award. Thanks to NeurIPS!
  • 2023/09 [NeurIPS'23] Two papers accepted by NeurIPS 2023: SnapFusion and a work about weakly-supervised latent graph inference led by Jianglin. 2024/02 Gave a talk at ASU about SnapFusion [Slides]. Thanks for the warm invitation from Maitreya Jitendra Patel, Sheng Cheng, and Prof. Yezhou Yangheart!
  • 2023/07 [ICCV'23] One paper about sparse network training for efficient image super-resolution is accepted by ICCV'23. Congrats to Jiamian!
  • 2023/06 [Internship'23] Start full-time summer internship at Google AR.
  • 2023/06 [Preprint] 🔥🔥We are excited to present SnapFusion, a brand-new efficient Stable Diffusion model on mobile devices. SnapFusion can generate a 512x512 image from text in only 1.84s on iPhone 14 Pro, which is the fastest🚀 on-device SD model as far as we know! Give a talk at JD Health about this work [Slides].
  • 2023/05 [Talk] Give a talk at ZJUI (ZJU-UIUC Institute) on the recent advances in efficient neural light field (NeLF), featuring two of our recent NeLF papers (R2L and MobileR2L). [Slides]
  • 2023/05 [Award] Recognized as CVPR'23 Outstanding Reviewer (3.3%). Thanks to CVPR and the ACs!
  • 2023/04 [TPAMI'23] Extension of our NeurIPS'21 spotlight paper ASSL, "Global Aligned Structured Sparsity Learning for Efficient Image Super-Resolution", is accepted by TPAMI (IF=24.31). Code will be relased to the same repo.
  • 2023/03 [Award] Received ICLR'23 Travel Award. Thanks to ICLR!
  • 2023/02 [CVPR'23] 2 papers accepted by CVPR'23: (1) MobileR2L [Code] , congrats to Junli! MobileR2L is a blazing fast🚀 neural rendering model designed for mobile devices: It can render 1008x756 images at 56fps on iPhone13. (2) Frame Flexible Network [Code], congrats to Yitian!
  • 2023/01 [ICLR'23] 2 papers accpeted by ICLR'23: Trainabaility Preserveing Neural Pruning (TPP) and Image as Set of Points (Oral, top-5%).
  • 2023/01 [Internship'23] Start part-time internship at Snap, luckily working with the Creative Vision team again. 2023/09 Update: The paper of this internship, SnapFusion, is accepted by NeurIPS 2023! Thanks to my coauthors!🎉
  • 2023/01 [Preprint] Check out our preprint work that deciphers the so confusing benchmark situation in neural network (filter) pruning: Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning [Code]. Also give a talk @UT Austin about this work. Thanks for the warm invitation from Dr. Shiwei Liu and Prof. Atlas Wang!
  • 2022/10 [Award] Received NeurIPS'22 Scholar Award. Thanks to NeurIPS!
  • 2022/09 [NeurIPS'22] 3 papers accepted by NeurIPS'22: One under my lead (which was my 1st internship work at MERL in 2020 summer. Rejected 4 times. Now finally I close the loop. Thanks to my co-authors and the reviewers!), two collaborations. Code: Good-DA-in-KD, PEMN, AFNet.
  • 2022/09 [TIP'22] One journal paper "Semi-supervised Domain Adaptive Structure Learning" accepted by TIP. Congtrats to Can!
  • 2022/07 [ECCV'22] We present the first residual MLP network to represent neural light field (NeLF) for efficient novel view synthesis. Check our webpage and ArXiv!
  • 2022/05 [Award] Received Northeastern PhD Network Travel Award. Thanks to Northeastern!
  • 2022/04 [IJCAI'22] We offer the very first survey paper on Pruning at Initialization, accepted by IJCAI'22 [ArXiv] [Paper Collection].
  • 2022/01 [ICLR'22] Two papers on neural network sparsity accepted by ICLR'22. One is about efficient image super-resolution (SRP), the other about lottery ticket hypothsis (DLTH).
  • 2021/09 [NeurIPS'21] One paper on efficient image super-resolution is accepted by NeurIPS'21 as a Spotlight (<3%) paper! [Code]
  • 2021/06 [Internship'21] Start summer internship at Snap Inc., working with the fantastic Creative Vision team.
  • 2021/01 [ICLR'21] One paper about neural network pruning accepted by ICLR'21 as poster. [ArXiv] [Code]
  • 2020/06 [Internship'20] Start summer internship at MERL, working with Dr. Mike Jones and Dr. Suhas Lohit. (2022/09 Update: Finally, paper of this project accpeted by NeurIPS'22 -- two good years have passed, thank God..!)
  • 2020/02 [CVPR'20] One paper about model compression for ultra-resolution neural style transfer "Collaborative Distillation for Ultra-Resolution Universal Style Transfer" is accepted by CVPR'20 [Code].
  • 2020/01 [MLSys'20] 2019 summer intern paper accepted by MLSys 2020. (Project: MNN from Alibaba, one of the fastest mobile AI engines on this planet. Welcome trying!)
  • 2019/12 [JSTSP'19] One journal paper "Structured Pruning for Efficient Convolutional Neural Networks via Incremental Regularization" accepted by IEEE JSTSP.
  • 2019/09 Join SMILE Lab at Northeastern University (Boston, USA) to pursue my Ph.D. degree.
  • 2019/07 [Internship'19] Start summer internship at Taobao of Alibaba Group ( Hangzhou, China).
  • 2019/06 Graduate with M.Sc. degree from Zhejiang University (Hangzhou, China).
My Research [Google Scholar]
Don't Judge by the Look: A Motion Coherent Augmentation for Video Recognition
Yitian Zhang, Yue Bai, Huan Wang, Yizhou Wang, Yun Fu
In ICLR, 2024
ArXiv
Project Webpage
Code (to be released; please stay tuned)
SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Seconds
Yanyu Li*, Huan Wang*, Qing Jin*, Ju Hu, Pavlo Chemerys, Yun Fu, Yanzhi Wang, Sergey Tulyakov, Jian Ren* (*Equal Contribution)
In NeurIPS, 2023
ArXiv
Project Webpage
Code (may not release in a short period due to IP issues)
Latent Graph Inference with Limited Supervision
Jianglin Lu, Yi Xu, Huan Wang, Yue Bai, Yun Fu
In NeurIPS, 2023
Arxiv
Code
Iterative Soft Shrinkage Learning for Efficient Image Super-Resolution
Jiamian Wang, Huan Wang, Yulun Zhang, Yun Fu, Zhiqiang Tao
In ICCV, 2023
Arxiv
Code
Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning
Huan Wang, Can Qin, Yue Bai, Yun Fu
Preprint, 2023
ArXiv
Code
Global Aligned Structured Sparsity Learning for Efficient Image Super-Resolution
Huan Wang*, Yulun Zhang*, Can Qin, Luc Van Gool, Yun Fu (*Equal Contribution)
TPAMI, 2023
PDF
Code
Real-Time Neural Light Field on Mobile Devices
Junli Cao, Huan Wang, Pavlo Chemerys, Vladislav Shakhray, Ju Hu, Yun Fu, Denys Makoviichuk, Sergey Tulyakov, Jian Ren
In CVPR, 2023
Project Webpage
ArXiv
Code
Trainability Preserving Neural Pruning
Huan Wang, Yun Fu
In ICLR, 2023
OpenReivew
ArXiv
PyTorch Code
Image as Set of Points
Xu Ma, Yuqian Zhou, Huan Wang, Can Qin, Bin Sun, Chang Liu, Yun Fu
In ICLR (Oral, 5%), 2023
Project Webpage
OpenReview
PyTorch Code
What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective
Huan Wang, Suhas Lohit, Mike Jones, Yun Fu
In NeurIPS, 2022
Project Webpage
ArXiv
PyTorch Code
Parameter-Efficient Masking Networks
Yue Bai, Huan Wang, Xu Ma, Yitian Zhang, Zhiqiang Tao, Yun Fu
In NeurIPS, 2022
ArXiv
PyTorch Code
Look More but Care Less in Video Recognition
Yitian Zhang, Yue Bai, Huan Wang, Yi Xu, Yun Fu
In NeurIPS, 2022
ArXiv
PyTorch Code
R2L: Distilling Neural Radiance Field to Neural Light Field for Efficient Novel View Synthesis
Huan Wang, Jian Ren, Zeng Huang, Kyle Olszewski, Menglei Chai, Yun Fu, Sergey Tulyakov
In ECCV, 2022
Project Webpage
ArXiv
PyTorch Code
Recent Advances on Neural Network Pruning at Initialization
Huan Wang, Can Qin, Yue Bai, Yulun Zhang, Yun Fu
In IJCAI, 2022
ArXiv
Paper Collection
Learning Efficient Image Super-Resolution Networks via Structure-Regularized Pruning
Huan Wang*, Yulun Zhang*, Can Qin, Yun Fu (*Equal Contribution)
In ICLR, 2022
Open Review
PyTorch Code
Dual Lottery Ticket Hypothesis
Yue Bai, Huan Wang, Zhiqiang Tao, Kunpeng Li, Yun Fu
In ICLR, 2022
Open Review, ArXiv
PyTorch Code
Aligned Structured Sparsity Learning for Efficient Image Super-Resolution
Huan Wang*, Yulun Zhang*, Can Qin, Yun Fu (*Equal Contribution)
In NeurIPS (Spotlight, <3%), 2021
Camera Ready
PyTorch Code
Neural Pruning via Growing Regularization
Huan Wang, Can Qin, Yulun Zhang, Yun Fu
In ICLR, 2021
ArXiv, OpenReview
PyTorch Code
Collabrotive Distillation for Ultra-Resolution Universal Style Transfer
Huan Wang, Yijun Li, Yuehai Wang, Haoji Hu, Ming-Hsuan Yang
In CVPR, 2020
ArXiv, Camera Ready
PyTorch Code
MNN: A Universal and Efficient Inference Engine
Xiaotang Jiang, Huan Wang, Yiliu Chen, Ziqi Wu, et al.
In MLSys (Oral), 2020
ArXiv
Code
Structured Pruning for Efficient ConvNets via Incremental Regularization
Huan Wang, Xinyi Hu, Qiming Zhang, Yuehai Wang, Lu Yu, Haoji Hu
In NeurIPS Workshop, 2018; IJCNN, 2019 (Oral); Journal extension to IEEE JSTSP, 2019
NeurIPS Workshop, IJCNN, JSTSP
Caffe Code
Structured Probabilistic Pruning for Convolutional Neural Network Acceleration
Huan Wang*, Qiming Zhang*, Yuehai Wang, Haoji Hu (*Equal Contribution)
In BMVC, 2018 (Oral)
ArXiv, Camera Ready
Caffe Code
Invited Talks
Professional Services
  • Journal Reviewer - TPAMI, IJCV, TIP, TNNLS, PR, IoT, JSTSP, TCSVT, Neurocomputing, NCAA, PLOS ONE, CIM, APIN, Advances in Statistical Analysis (AStA), Scientific Programming, The Computer Journal (COMPJ), TBIOM, MTAP, AI Communications (AIC), etc.
  • Conference Reviewer - CVPR'22-24, ECCV/ICCV'22-24, ICML'22/24, ICLR'22/24, NeurIPS'22-23, AAAI'22-24, IJCAI'23-24, MLSys'23, SIGGRAPH Asia'23, WACV'24, FG'24, AISTATS'24, CPAL'24, ACCV'24, etc.

(This webpage template is stolen from Jon Barron.)