Liuhao Ge
Computer Vision and Pattern Recognition · 2016–2019
A researcher in the Science corpus: 5 papers; trusts 423 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 149 citations into it; #7,712 of 21,575 by trust here, #6,873 by citations
- Human-Computer Interaction — 84 citations into it; #474 of 2,253 by trust here, #290 by citations
- Control and Systems Engineering — 58 citations into it; #3,017 of 8,257 by trust here, #1,769 by citations
- 3D Vision & Pose — 31 citations into it; #571 of 689 by trust here, #529 by citations
- Artificial Intelligence — 29 citations into it; #30,240 of 35,345 by trust here, #16,771 by citations
- Computational Mechanics — 16 citations into it
- Biomedical Engineering — 11 citations into it
Whom Liuhao Ge trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ross B. Girshick
- Kaiming He
- Yann LeCun
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Diederik P. Kingma
- Christian Szegedy
- Andrew Zisserman
- Ilya Sutskever
Who trusts Liuhao Ge overall
- Gyeongsik Moon
- Kyoung Mu Lee
- Long Zhao
- Munir Oudah
- Fanqing Lin
- Yujun Cai
- Linlin Yang
- Yuxiao Zhou
- Franziska Mueller
- Hongsuk Choi
Papers from Liuhao Ge's perspective
Ordered by how strongly the researchers Liuhao Ge trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- 3D Hand Shape and Pose Estimation From a Single RGB Image (2019) — 504 citations
- Weakly-Supervised 3D Hand Pose Estimation from Monocular RGB Images (2018) — 318 citations
- Robust 3D Hand Pose Estimation in Single Depth Images: From Single-View CNN to Multi-View CNNs (2016) — 297 citations
- Exploiting Spatial-Temporal Relationships for 3D Pose Estimation via Graph Convolutional Networks (2019) — 520 citations
- Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals (2017) — 46 citations