Xinyu Liu

Computer Vision and Pattern Recognition · with Goldberg · 2017–2018

A researcher in the Science corpus: 3 papers; trusts 38 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 49 citations into it
• Control and Systems Engineering — 44 citations into it; #3,511 of 8,257 by trust here, #536 by citations
• Artificial Intelligence — 29 citations into it
• Robotics & Control — 24 citations into it; #309 of 609 by trust here, #155 by citations
• Aerospace Engineering — 21 citations into it
• Biomedical Engineering — 15 citations into it; #4,111 of 10,734 by trust here, #2,547 by citations
• Geology — 8 citations into it
• Human-Computer Interaction — 8 citations into it

Whom Xinyu Liu trusts overall

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

1. Jeffrey Mahler
2. Edward Johns
3. Daniel Kappler
4. Alex Krizhevsky
5. Walter Wohlkinger
6. Ashutosh Saxena
7. Jeannette Bohg
8. Ian Lenz
9. Geoffrey E. Hinton
10. Kaiming He

Who trusts Xinyu Liu overall

1. Andy Zeng
2. Jeffrey Mahler

Papers from Xinyu Liu's perspective

Ordered by how strongly the researchers Xinyu Liu 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. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
4. ImageNet: A large-scale hierarchical image database
5. Histograms of oriented gradients for human detection
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Attention is All you Need (Neural Information Processing Systems)
9. Long Short-Term Memory
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics (2017) — 1,418 citations
• Dex-Net 3.0: Computing Robust Vacuum Suction Grasp Targets in Point Clouds Using a New Analytic Model and Deep Learning (2018) — 244 citations
• Dex-Net 3.0: Computing Robust Robot Suction Grasp Targets in Point Clouds using a New Analytic Model and Deep Learning (2017) — 133 citations