Yebin Liu

Computer Vision and Pattern Recognition · 2009–2022

A researcher in the Science corpus: 12 papers; trusts 917 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 330 citations into it; #7,643 of 21,575 by trust here, #6,206 by citations
• Computational Mechanics — 124 citations into it; #3,300 of 10,001 by trust here, #1,693 by citations
• Computer Graphics and Computer-Aided Design — 100 citations into it
• 3D Vision & Pose — 43 citations into it
• Control and Systems Engineering — 41 citations into it
• Aerospace Engineering — 35 citations into it
• Artificial Intelligence — 29 citations into it
• Model Architectures — 17 citations into it

Whom Yebin Liu trusts overall

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

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

Who trusts Yebin Liu overall

1. Zerong Zheng
2. Xiaoyan Hu
3. Zeng Huang
4. Kaiwen Guo
5. Yuliang Xiu
6. Fei Han
7. Nikolaos Sarafianos
8. Mengqi Ji
9. Tao Yu
10. Qionghai Dai

Papers from Yebin Liu's perspective

Ordered by how strongly the researchers Yebin 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• SurfaceNet: An End-to-End 3D Neural Network for Multiview Stereopsis (2017) — 455 citations
• DeepHuman: 3D Human Reconstruction From a Single Image (2019) — 374 citations
• Markerless motion capture of interacting characters using multi-view image segmentation (2011) — 164 citations
• Learning High-level Prior with Convolutional Neural Networks for Semantic Segmentation (2015) — 10 citations
• PyMAF: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop (2021) — 393 citations
• Tensor4D: Efficient Neural 4D Decomposition for High-Fidelity Dynamic Reconstruction and Rendering (2022) — 300 citations
• Function4D: Real-time Human Volumetric Capture from Very Sparse Consumer RGBD Sensors (2021) — 409 citations
• PaMIR: Parametric Model-Conditioned Implicit Representation for Image-Based Human Reconstruction (2020) — 376 citations
• DoubleFusion: Real-Time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor (2018) — 298 citations
• Light Field Image Processing: An Overview (2017) — 534 citations
• Free-Viewpoint Video of Human Actors Using Multiple Handheld Kinects (2013) — 33 citations
• Continuous depth estimation for multi-view stereo (2009) — 107 citations