Huaping Liu

Computer Vision and Pattern Recognition · with Sun · 2006–2022

A researcher in the Science corpus: 12 papers; trusts 1,366 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 304 citations into it; #8,827 of 21,575 by trust here, #4,174 by citations
• Artificial Intelligence — 161 citations into it; #17,959 of 35,345 by trust here, #23,077 by citations
• Representation & Self-Supervised Learning — 43 citations into it
• Model Architectures — 29 citations into it
• Aerospace Engineering — 23 citations into it
• Media Technology — 22 citations into it
• Evaluation & Benchmarks — 21 citations into it
• Optimization & Training — 14 citations into it; #1,568 of 2,601 by trust here, #2,484 by citations

Whom Huaping Liu trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. David G. Lowe
6. Yann LeCun
7. Karen Simonyan
8. Yoshua Bengio
9. Shaoqing Ren
10. Andrew Zisserman

Who trusts Huaping Liu overall

1. Amir Shahroudy
2. Liyuan Wang
3. Sen Lin
4. Yifan Zhang
5. Arka Pal
6. Shawn Shan
7. Tian-Tsong Ng
8. Chaoning Zhang
9. Jiale Cao
10. Rowan Zellers

Papers from Huaping Liu's perspective

Ordered by how strongly the researchers Huaping 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. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
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

• Deep Feature Pyramid Reconfiguration for Object Detection (2018) — 218 citations
• RON: Reverse Connection with Objectness Prior Networks for Object Detection (2017) — 419 citations
• FoveaBox: Beyound Anchor-Based Object Detection (2019) — 774 citations
• FoveaBox: Beyond Anchor-based Object Detector (2019) — 226 citations
• Understanding the Behaviour of Contrastive Loss (2020) — 894 citations
• RGB-D action recognition using linear coding (2015) — 18 citations
• Continual Learning with Recursive Gradient Optimization (2022) — 56 citations
• Embodied Semantic Scene Graph Generation (2021) — 37 citations
• Multi-agent Embodied Question Answering in Interactive Environments (2020) — 34 citations
• Scene-Level Geographic Image Classification Based on a Covariance Descriptor Using Supervised Collaborative Kernel Coding (2016) — 6 citations
• Scalable Gaussian Process Regression Using Deep Neural Networks (2015) — 70 citations
• Robust control of uncertain discrete-time Markovian jump systems with actuator saturation (2006) — 71 citations