Bokui (William) Shen

Computer Vision and Pattern Recognition · with Li · 2018–2023

A researcher in the Science corpus: 6 papers; trusts 505 researchers and is trusted by 54 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 206 citations into it; #4,164 of 21,575 by trust here, #3,141 by citations
• Artificial Intelligence — 130 citations into it; #17,301 of 35,345 by trust here, #4,526 by citations
• Reinforcement Learning — 70 citations into it
• Control and Systems Engineering — 57 citations into it
• Robotics & Control — 55 citations into it
• Aerospace Engineering — 47 citations into it
• Representation & Self-Supervised Learning — 33 citations into it; #1,961 of 3,145 by trust here, #806 by citations
• Optimization & Training — 12 citations into it

Whom Bokui (William) Shen trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Yoshua Bengio
6. Ross B. Girshick
7. Yann LeCun
8. Ilya Sutskever
9. Jitendra Malik
10. Angel X. Chang

Who trusts Bokui (William) Shen overall

1. Fei Xia
2. Alexander Sax
3. Chengshu Li
4. Luca Weihs
5. Simon Vandenhende
6. Michael Crawshaw
7. Yang Zheng
8. Amir Zamir
9. Jeffrey O. Zhang
10. Cuong V Nguyen

Papers from Bokui (William) Shen's perspective

Ordered by how strongly the researchers Bokui (William) Shen trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Taskonomy: Disentangling Task Transfer Learning (2018) — 1,404 citations
• Interactive Gibson Benchmark: A Benchmark for Interactive Navigation in Cluttered Environments (2019) — 213 citations
• iGibson 2.0: Object-Centric Simulation for Robot Learning of Everyday Household Tasks (2021) — 329 citations
• iGibson 1.0: A Simulation Environment for Interactive Tasks in Large Realistic Scenes (2020) — 246 citations
• PointOdyssey: A Large-Scale Synthetic Dataset for Long-Term Point Tracking (2023) — 294 citations
• iGibson, a Simulation Environment for Interactive Tasks in Large Realistic Scenes (2020) — 57 citations