Yunhui Liu
Computer Vision and Pattern Recognition · IEEE International Conference on Computer Vision · 2003–2021
A researcher in the Science corpus: 6 papers; trusts 658 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 134 citations into it; #15,921 of 21,575 by trust here, #10,500 by citations
- Artificial Intelligence — 69 citations into it
- Representation & Self-Supervised Learning — 39 citations into it
- Evaluation & Benchmarks — 15 citations into it
- Geology — 13 citations into it
- Model Architectures — 9 citations into it
- Robotics & Control — 6 citations into it
- Cognitive Neuroscience — 5 citations into it
Whom Yunhui Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Andrew Zisserman
- Diederik P. Kingma
- Ross B. Girshick
- Karen Simonyan
- Yoshua Bengio
- Yann LeCun
- Ilya Sutskever
Who trusts Yunhui Liu overall
Papers from Yunhui Liu's perspective
Ordered by how strongly the researchers Yunhui Liu 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
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Self-Supervised Spatio-Temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics (2019) — 223 citations
- Self-supervised Video Representation Learning by Pace Prediction (2020) — 263 citations
- PlaTe: Visually-Grounded Planning With Transformers in Procedural Tasks (2021) — 68 citations
- LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis (2018) — 343 citations
- Uncalibrated visual servoing of robots using a depth-independent interaction matrix (2006) — 296 citations
- Dynamic sliding PID control for tracking of robot manipulators: theory and experiments (2003) — 335 citations