Bineng Zhong

Computer Vision and Pattern Recognition · 2016–2024

A researcher in the Science corpus: 9 papers; trusts 1,256 researchers and is trusted by 86 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 394 citations into it; #3,146 of 21,575 by trust here, #2,240 by citations
• Media Technology — 116 citations into it; #193 of 3,621 by trust here, #120 by citations
• Artificial Intelligence — 110 citations into it; #34,527 of 35,345 by trust here, #25,040 by citations
• Evaluation & Benchmarks — 42 citations into it
• Model Architectures — 33 citations into it
• Biomedical Engineering — 25 citations into it
• Generative Models — 23 citations into it
• Computational Mechanics — 16 citations into it

Whom Bineng Zhong trusts overall

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

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

Who trusts Bineng Zhong overall

1. Kai Zhang
2. Jingyun Liang
3. Jinjin Gu
4. Syed Waqas Zamir
5. Yulun Zhang
6. Radu Timofte
7. Jie Liu
8. Saeed Anwar
9. Chao Dong
10. Yochai Blau

Papers from Bineng Zhong's perspective

Ordered by how strongly the researchers Bineng Zhong trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Residual Dense Network for Image Super-Resolution (2018) — 3,919 citations
• Image Super-Resolution Using Very Deep Residual Channel Attention Networks (2018) — 5,405 citations
• Residual Non-local Attention Networks for Image Restoration (2019) — 777 citations
• Residual Dense Network for Image Restoration (2018) — 853 citations
• Siamese Box Adaptive Network for Visual Tracking (2020) — 856 citations
• CNNTracker: Online discriminative object tracking via deep convolutional neural network (2016) — 101 citations
• A Comprehensive Survey of Vision-Based Human Action Recognition Methods (2019) — 483 citations
• ODTrack: Online Dense Temporal Token Learning for Visual Tracking (2024) — 300 citations
• What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation (2020) — 149 citations