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Dr. Shuchang ZHOU (周舒畅)

个人信息

演讲

  • 硬件-软件协同设计在计算机视觉中的应用 (PDF), 清华大学, 2022年4月
  • 神经网络与计算机架构的协同进化 ([PDF](Coevolution of Neural Network and Computer Architecture(3).pdf)), 2019年8月
  • 未来三年计算机架构的推测 (PDF), 2018年1月20日
  • 使用Haskell和FPGA模拟的量子计算 ([PDF](Quantum Computing with Haskell and FPGA simulation.pdf), GitHub), 2018年1月18日
  • 量化神经网络在智能嵌入式视觉中的应用 ([PDF](Smart Embedded Vision with Low Bitwidth Networks.pdf)), 清华大学, 2017年7月8日
  • 深度学习中的实用方法论 ([PDF](Practical Methodology in Deep Learning.pdf)), 北京大学, 2017年4月
  • 神经网络近似 ([PDF](Neural Network Approximation.pdf)), 清华大学姚班, 2016年11月
  • 指针级别分析 (PDF), 2009年

精选论文

  • (2025) Step-audio: 智能语音交互中的统一理解与生成
  • (ECCV'24) Chat-edit-3d: 通过文本提示进行交互式3D场景编辑
  • (ICCAD'23) Sole: 用于高效Transformer推理的Softmax和LayerNorm的硬件-软件协同设计
  • (AAAI'23) One is all: 通过渐进式体积蒸馏桥接神经辐射场架构之间的差距
  • (2023) Occdepth: 一种基于3D占用估计的3D语义场景补全方法
  • (ICCV'23) Occ$^2$Net: 基于3D占用估计的遮挡区域图像匹配
  • (CVPR'23 highlight) Xiaotao Hu, 等. "A Dynamic Multi-Scale Voxel Flow Network for Video Prediction." (arxiv, github)
  • (CVPR'23 highlight) Shengchao Zhou, 等. "UniDistill: A Universal Cross-Modality Knowledge Distillation Framework for 3D Object Detection in Bird’s-Eye View." (arxiv, github)
  • (CVPR'23) Yun-Hao Cao, 等. "Three Guidelines You Should Know for Universally Slimmable Self-Supervised Learning." (arxiv, github)
  • (AAAI oral) Shuangkang Fang, 等. "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，等: RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation. (arxiv, github)
  • (EACL) Yuekai Zhao, 等. Multi-split Reversible Transformers Can Enhance Neural Machine Translation
  • (IJCAI) Yang Lin, 等. "Fq-vit: Fully quantized vision transformer without retraining". (arxiv, github)
  • (EMNLP) Yuekai Zhao, 等. Active learning approaches to enhancing neural machine translation. (pdf)
  • (CVPR) Peibin Chen, 等. 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 等. "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
  • 更多论文请见Google Scholar (引用7000+)
  • 有两个项目达到 4000+ Github star, 分别是 Step-Audio 和 RIFE.

竞赛

研究领域

  • 机器学习与人工智能
  • 计算机架构
  • 随机优化

学术服务

最后更新: 2025年3月