Huimin Ma

Computer Vision and Pattern Recognition · with Chen · 2015–2018

A researcher in the Science corpus: 8 papers; trusts 1,019 researchers and is trusted by 550 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 192 citations into it; #1,813 of 21,575 by trust here, #1,567 by citations
• Artificial Intelligence — 72 citations into it
• Aerospace Engineering — 37 citations into it; #203 of 6,421 by trust here, #250 by citations
• Reinforcement Learning — 28 citations into it
• 3D Vision & Pose — 21 citations into it; #176 of 689 by trust here, #91 by citations
• Evaluation & Benchmarks — 19 citations into it
• Environmental Engineering — 11 citations into it
• Model Architectures — 10 citations into it

Whom Huimin Ma trusts overall

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

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

Who trusts Huimin Ma overall

1. Binh Yang
2. Lei Tai
3. Shaoshuai Shi
4. Ming Liang
5. Yin Zhou
6. Bo Li
7. Raquel Urtasun
8. Xinzhu Ma
9. Wenjie Luo
10. Xiaozhi Chen

Papers from Huimin Ma's perspective

Ordered by how strongly the researchers Huimin Ma 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. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
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

• Multi-view 3D Object Detection Network for Autonomous Driving (2016) — 3,211 citations
• 3D Object Proposals for Accurate Object Class Detection (2015) — 904 citations
• Monocular 3D Object Detection for Autonomous Driving (2016) — 1,014 citations
• 3D Object Proposals Using Stereo Imagery for Accurate Object Class Detection (2016) — 404 citations
• Improving object proposals with multi-thresholding straddling expansion (2015) — 84 citations
• Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features (2018) — 320 citations
• Pretraining Deep Actor-Critic Reinforcement Learning Algorithms With Expert Demonstrations (2018) — 39 citations
• Survival-Oriented Reinforcement Learning Model: An Effcient and Robust Deep Reinforcement Learning Algorithm for Autonomous Driving Problem (2017) — 9 citations