Dr. Shuchang ZHOU

Talks

Hardware-software co-design for Computer Vision ( PDF), Tsinghua University, Apr. 2022
Some Recent Advances in Computer Vision (near 2021) ( PDF, Bilibili (Chinese) ), Tsinghua University, Oct. 2021
Coevolution of Neural Network and Computer Architecture ( PDF ), Aug. 2019
Speculations about Computer Architecture in Next Three Years ( PDF), Jan. 20, 2018
Quantum Computing with Haskell and FPGA simulation ( PDF , GitHub ), Jan. 18, 2018
Smart Embedded Vision with Quantized Neural Network ( PDF ), Tsinghua University, Jul. 8 2017
Practical Methodology in Deep Learning ( PDF ), Peking University, Apr. 2017
Neural Network Approximations ( PDF ), Yao Class, Tsinghua University, Nov. 2016
Pointer Level Analysis ( PDF ), 2009

Selected Publications

(CVPR'23 highlight) Xiaotao Hu, et al. "A Dynamic Multi-Scale Voxel Flow Network for Video Prediction." ( arxiv, github)
(CVPR'23 highlight) Shengchao Zhou, et al. "UniDistill: A Universal Cross-Modality Knowledge Distillation Framework for 3D Object Detection in Bird’s-Eye View." ( arxiv, github)
(CVPR'23) Yun-Hao Cao, et al. "Three Guidelines You Should Know for Universally Slimmable Self-Supervised Learning." ( arxiv, github)
(AAAI oral) Shuangkang Fang, et al. "One is All: Bridging the Gap Between Neural Radiance Fields Architectures with Progressive Volume Distillation." ( arxiv, github)
(ECCV oral) Yun-Hao Cao, Peiqin Sun, Yechang Huang, Jianxin Wu and Shuchang Zhou: Synergistic Self-supervised and Quantization Learning. ( arxiv, github)
(ECCV) Zhewei Huang, Tianyuan Zhang, Wen Heng, Boxin Shi, Shuchang Zhou: RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation. ( arxiv, github)
(EACL) Yuekai Zhao, et al. Multi-split Reversible Transformers Can Enhance Neural Machine Translation
(IJCAI) Yang Lin, et al. "Fq-vit: Fully quantized vision transformer without retraining". ( arxiv, github)
(EMNLP) Yuekai Zhao, et al. Active learning approaches to enhancing neural machine translation. ( pdf )
(CVPR) Peibin Chen, et al. Data-efficient semi-supervised learning by reliable edge mining
(ICCV) Zhewei Huang, Wen Heng, Shuchang Zhou: Learning to Paint with Model-based Deep Reinforcement Learning. ( arxiv, github)
(CVPR) Xinyu Zhou, Cong Yao, He Wen, Yuzhi Wang, Shuchang Zhou, Weiran He, Jiajun Liang: EAST: An Efficient and Accurate Scene Text Detector. ( arxiv)
(BMVC) Shuchang Zhou, Taihong Xiao, Yi Yang, Dieqiao Feng, Qinyao He, Weiran He: GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data. ( arxiv , slide , GitHub )
Shuchang Zhou, Yuxin Wu, Zekun Ni, Xinyu Zhou, He Wen, Yuheng Zou: DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients. ( arxiv , GitHub )
(ACL) Fangtao Li et al. "Deceptive answer prediction with user preference graph"
Shuchang Zhou: An Efficient Simulation Algorithm for Cache of Random Replacement Policy. PDF, slide , GitHub
Open64 on MIPS: porting and enhancing Open64 for Loongson II
More at Google Scholar

Competitions

1st place in the listening head generation track and 2nd place in the talking head generation track, ACM Multimedia ViCo 2022 Conversational Head Generation Challenge, report
"Nuri" won the 1st place in NeurIPS'21 Machine Learning for Combinatorial Optimization Dual Task track. Code
"Megvii-hzwer" won the 2nd place in NIPS'17 Learning to Run Challenge , a competition on teaching a skeleton to run as fast as possible. We proposed the Actor-Critic Ensemble (ACE) method ( PDF , Github).
"Megvii" won the 1st place in all tracks in NIST TRAIT '16 , a competition on Text Recognition in the wild (OCR).

Research Areas

Machine Learning and Artificial Intelligence
Computer Architecture
Stochastic Optimization

Academic Service

(in Chinese) Co-organize a joint course for three years on Deep Learning and Computer Vision at Peking University.

(in Chinese) Lectures at Tsinghua University on CV and Quantized Neural Network link

Reviewer of AAAI, NIPS, IJCAI, IPDPS, TIP, JSTSP, TNNLS, TPAMI, TVLSI, and serving on JMLR editorial board.

Last update: Apr., 2022.