Zhuang Liu

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Kilian WeinbergerCornell UniversityDirección de correo verificada de cornell.edu
Laurens van der MaatenDistinguished Research Scientist, Llama Team, Meta AIDirección de correo verificada de meta.com
Saining XieAssistant Professor at the Courant Institute, New York UniversityDirección de correo verificada de nyu.edu
Trevor DarrellProfessor of Computer Science, U.C. BerkeleyDirección de correo verificada de eecs.berkeley.edu
Zhiqiang ShenAssistant Professor at Mohamed bin Zayed University of Artificial IntelligenceDirección de correo verificada de mbzuai.ac.ae
Jianguo LiDirector, Ant GroupDirección de correo verificada de antgroup.com
Christoph FeichtenhoferMeta, FAIRDirección de correo verificada de fb.com
Chao-Yuan WuWorld LabsDirección de correo verificada de meta.com
Hanzi MaoResearch Scientist, NvidiaDirección de correo verificada de nvidia.com
Yu SunPostdoc, Stanford UniversityDirección de correo verificada de cs.stanford.edu
Xiaolong WangAssistant Professor, UC San DiegoDirección de correo verificada de ucsd.edu
Mingjie SunCarnegie Mellon UniversityDirección de correo verificada de cs.cmu.edu
Xinlei ChenFAIR, MetaDirección de correo verificada de meta.com
Tinghui ZhouRoblox, Foundation AIDirección de correo verificada de roblox.com
Bingyi KangResearch Scientist @ TikTokDirección de correo verificada de sea.com
Rohit GirdharResearch Scientist, GenAI, MetaDirección de correo verificada de fb.com
Yurong ChenSr. Principal AI Scientist / Research Director, Intel Labs ChinaDirección de correo verificada de intel.com
Ronghang HuResearch Scientist, AI at MetaDirección de correo verificada de meta.com
Sanghyun WooGoogle DeepMindDirección de correo verificada de google.com
Shoubhik DebnathFAIR, AI at MetaDirección de correo verificada de fb.com

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Zhuang Liu

Research Scientist, FAIR, Meta

Dirección de correo verificada de berkeley.edu - Página principal

Deep Learning Neural Networks Computer Vision Machine Learning


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Densely Connected Convolutional Networks Z Liu, G Huang, L Maaten, KQ Weinberger Computer Vision and Pattern Recognition (CVPR), 2017, 2017	52078*	2017
A ConvNet for the 2020s Z Liu, H Mao, CY Wu, C Feichtenhofer, T Darrell, S Xie Computer Vision and Pattern Recognition (CVPR), 2022, 2022	7063	2022
Learning Efficient Convolutional Networks through Network Slimming Z Liu, J Li, Z Shen, G Huang, S Yan, C Zhang International Conference on Computer Vision (ICCV), 2017, 2017	3191	2017
Deep Networks with Stochastic Depth G Huang, Y Sun, Z Liu, D Sedra, KQ Weinberger European Conference on Computer Vision (ECCV), 2016, 2016	2896	2016
Rethinking the Value of Network Pruning Z Liu, M Sun, T Zhou, G Huang, T Darrell International Conference on Learning Representations (ICLR), 2019, 2019	1838	2019
Few-shot Object Detection via Feature Reweighting B Kang, Z Liu, X Wang, F Yu, J Feng, T Darrell International Conference on Computer Vision (ICCV), 2019, 2019	943	2019
Test-time Training with Self-supervision for Generalization under Distribution Shifts Y Sun, X Wang, Z Liu, J Miller, A Efros, M Hardt International Conference on Machine Learning (ICML), 2020, 2020	910	2020
DSOD: Learning Deeply Supervised Object Detectors from Scratch Z Shen, Z Liu, J Li, YG Jiang, Y Chen, X Xue International Conference on Computer Vision (ICCV), 2017, 2017	905*	2017
Imagebind: One Embedding Space to Bind Them All R Girdhar, A El-Nouby, Z Liu, M Singh, KV Alwala, A Joulin, I Misra* Computer Vision and Pattern Recognition (CVPR), 2023, 2023	886*	2023
ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders S Woo, S Debnath, R Hu, X Chen, Z Liu, IS Kweon, S Xie Computer Vision and Pattern Recognition (CVPR), 2023, 2023	871*	2023
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning Y Chen, Z Liu, H Xu, T Darrell, X Wang International Conference on Computer Vision (ICCV), 2021, 2021	729*	2021
A Simple and Effective Pruning Approach for Large Language Models M Sun, Z Liu, A Bair, JZ Kolter International Conference on Learning Representations (ICLR), 2024, 2024	438	2024
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs S Tong, Z Liu, Y Zhai, Y Ma, Y LeCun, S Xie Computer Vision and Pattern Recognition (CVPR), 2024, 2024	224	2024
MSeg: A Composite Dataset for Multi-domain Semantic Segmentation J Lambert, Z Liu, O Sener, J Hayes, V Koltun Computer Vision and Pattern Recognition (CVPR), 2020, 2020	221	2020
Few Sample Knowledge Distillation for Efficient Network Compression T Li, J Li, Z Liu, C Zhang Computer Vision and Pattern Recognition (CVPR), 2020, 2020	191	2020
Un-mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning Z Shen, Z Liu, Z Liu, M Savvides, T Darrell, E Xing AAAI Conference on Artificial Intelligence (AAAI), 2022, 2022	138	2022
Regularization Matters in Policy Optimization--An Empirical Study on Continuous Control Z Liu, X Li, B Kang, T Darrell International Conference on Learning Representations (ICLR), 2021, 2021	98*	2021
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space A Chavan, Z Shen, Z Liu, Z Liu, KT Cheng, E Xing Computer Vision and Pattern Recognition (CVPR), 2022, 2022	83	2022
One-for-all: Generalized LoRA for Parameter-Efficient Fine-Tuning A Chavan, Z Liu, D Gupta, E Xing, Z Shen arXiv preprint arXiv:2306.07967, 2023	79	2023
Dropout Reduces Underfitting Z Liu, Z Xu, J Jin, Z Shen, T Darrell International Conference on Machine Learning (ICML), 2023, 2023	60	2023

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