Zhiwei Deng

Computer Vision and Pattern Recognition · 2015–2021

A researcher in the Science corpus: 6 papers; trusts 719 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 170 citations into it; #13,388 of 21,575 by trust here, #7,750 by citations
• Artificial Intelligence — 102 citations into it
• Model Architectures — 48 citations into it
• Generative Models — 22 citations into it
• Optimization & Training — 12 citations into it
• Natural Language Processing — 11 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Media Technology — 8 citations into it

Whom Zhiwei Deng trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Kaiming He
5. Yoshua Bengio
6. Yann LeCun
7. Ilya Sutskever
8. Christian Szegedy
9. Ross B. Girshick
10. Karen Simonyan

Who trusts Zhiwei Deng overall

1. Minsi Wang
2. Tianmin Shu
3. Yingzhen Li
4. Francesco Locatello
5. Fabien Baradel
6. Jason S. Hartford
7. Bingbing Ni
8. Jun Liu
9. Laurent Girin
10. Arash Vahdat

Papers from Zhiwei Deng's perspective

Ordered by how strongly the researchers Zhiwei Deng trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Hierarchical Deep Temporal Models for Group Activity Recognition (2016) — 518 citations
• Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition (2015) — 255 citations
• Factorized Variational Autoencoders for Modeling Audience Reactions to Movies (2017) — 50 citations
• Adaptive Appearance Rendering (2021)
• Sparsely Aggregated Convolutional Networks (2018) — 66 citations
• Structured Label Inference for Visual Understanding (2018) — 23 citations