Bing Shuai

Computer Vision and Pattern Recognition · 2015–2021

A researcher in the Science corpus: 11 papers; trusts 1,700 researchers and is trusted by 24 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 703 citations into it; #5,558 of 21,575 by trust here, #2,423 by citations
• Artificial Intelligence — 369 citations into it
• Model Architectures — 142 citations into it
• Signal Processing — 64 citations into it
• Optimization & Training — 60 citations into it
• Natural Language Processing — 55 citations into it
• Representation & Self-Supervised Learning — 45 citations into it
• Aerospace Engineering — 42 citations into it

Whom Bing Shuai trusts overall

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

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

Who trusts Bing Shuai overall

1. Heng Fan
2. Hojjat Salehinejad
3. Alberto Garcia-Garcia
4. Jiuxiang Gu
5. G. Wang
6. Fahad Lateef
7. Haibin Ling
8. Wenguan Wang
9. Liang Zheng
10. Qiuhong Ke

Papers from Bing Shuai's perspective

Ordered by how strongly the researchers Bing Shuai 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. ImageNet: A large-scale hierarchical image database
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
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

• A Siamese Long Short-Term Memory Architecture for Human Re-identification (2016) — 593 citations
• Context Contrasted Feature and Gated Multi-scale Aggregation for Scene Segmentation (2018) — 391 citations
• VidTr: Video Transformer Without Convolutions (2021) — 226 citations
• Recent advances in convolutional neural networks (2015) — 6,013 citations
• Semantic Segmentation With Context Encoding and Multi-Path Decoding (2020) — 148 citations
• Deep Level Sets for Salient Object Detection (2017) — 192 citations
• DAG-Recurrent Neural Networks for Scene Labeling (2015) — 153 citations
• Episodic CAMN: Contextual Attention-Based Memory Networks with Iterative Feedback for Scene Labeling (2017) — 15 citations
• Integrating parametric and non-parametric models for scene labeling (2015) — 53 citations
• Quaddirectional 2D-Recurrent Neural Networks For Image Labeling (2015) — 35 citations
• Exemplar based Deep Discriminative and Shareable Feature Learning for scene image classification (2015) — 69 citations