Huan Wang's Website

Huan Wang

Welcome to my webpage! My name is Huan Wang (Chinese: 王欢. My first name means "happiness or joy" in Chinese, a simple and ultimate wish from my parents). I am now a 4th-year Ph.D. candidate at SMILE Lab, Northeastern University (Boston, USA), advised by Prof. Yun (Raymond) Fu. Before that, I received my M.S. (2019) and B.E. (2016) degrees from Zhejiang University (Hangzhou, China), advised by Prof. Haoji Hu. During 2018 summer, I visited VLLab at University of California, Merced, luckily working with Prof. Ming-Hsuan Yang. I also actively collaborate with fatanstic industrial researchers from Snap / MERL / Meta / Alibaba Group, etc.

My research works orbit Efficient Deep Learning (a.k.a. Model Compression), spanning the most common image classifcation task (GReg, Pruning-at-Initialization Survey, TPP) to neural style transfer (Collaborative-Distillation, single image super-resolution (ASSL/GASSL, SRP) and 3D novel view synthesis / NeRF / NeLF (R2L, MobileR2L).

I do my best towards easily reproducible research.

Google Scholar / GitHub / LinkedIn / Twitter

News

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.
2023/01: [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]
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!
2022/04: [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]

	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 Shakhrai, 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

Talks

[01/06/2023] VITA Group @ UT Austin: Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning [Slides]
[09/30/2021] Data Lab @ NEU: Neural Pruning via Growing Regularization (ICLR'21) [Slides]

Professional Services

Journal Reviewer: IJCV, TIP, TNNLS, PR, JSTSP, Neurocomputing, etc.
Conference Reviewer: CVPR'22, ECCV'22, ICML'22, NeurIPS'22, ICLR'22, AAAI'23, IJCAI'23, CVPR'23, MLSys'23, ICCV'23, NeurIPS'23 etc.

(Stolen from Jon Barron)