Lihe Zhang
Computer Vision and Pattern Recognition · 2013–2021
A researcher in the Science corpus: 8 papers; trusts 1,044 researchers and is trusted by 120 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 249 citations into it; #2,824 of 21,575 by trust here, #2,525 by citations
- Cognitive Neuroscience — 60 citations into it; #5,334 of 10,852 by trust here, #4,819 by citations
- Sensory Systems — 33 citations into it; #9 of 760 by trust here, #19 by citations
- Artificial Intelligence — 32 citations into it
- Human-Computer Interaction — 19 citations into it
- Model Architectures — 16 citations into it
- Media Technology — 15 citations into it
- Evaluation & Benchmarks — 8 citations into it
Whom Lihe Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Karen Simonyan
- Geoffrey E. Hinton
- Alex Krizhevsky
- Ross B. Girshick
- Ming-Ming Cheng
- Andrew Zisserman
- Yoshua Bengio
- Diederik P. Kingma
- Yann LeCun
Who trusts Lihe Zhang overall
- Wenguan Wang
- Huchuan Lu
- Zhe Wu
- Junwei Han
- Youwei Pang
- Nian Liu
- Jianbing Shen
- Ming-Ming Cheng
- Deng-Ping Fan
- Ali Borji
Papers from Lihe Zhang's perspective
Ordered by how strongly the researchers Lihe Zhang 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
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Saliency Detection via Graph-Based Manifold Ranking (2013) — 2,484 citations
- Saliency Detection via Absorbing Markov Chain (2013) — 598 citations
- Saliency Detection via Dense and Sparse Reconstruction (2013) — 708 citations
- Detect Globally, Refine Locally: A Novel Approach to Saliency Detection (2018) — 391 citations
- A Stagewise Refinement Model for Detecting Salient Objects in Images (2017) — 416 citations
- Automatic Polyp Segmentation via Multi-scale Subtraction Network (2021) — 355 citations
- Multi-Scale Interactive Network for Salient Object Detection (2020) — 759 citations
- Suppress and Balance: A Simple Gated Network for Salient Object Detection (2020) — 518 citations