Junge Zhang
Computer Vision and Pattern Recognition · 2011–2019
A researcher in the Science corpus: 7 papers; trusts 947 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 186 citations into it; #8,769 of 21,575 by trust here, #6,737 by citations
- Artificial Intelligence — 74 citations into it
- Representation & Self-Supervised Learning — 25 citations into it; #2,126 of 3,145 by trust here, #2,691 by citations
- Generative Models — 22 citations into it; #1,433 of 1,956 by trust here, #1,435 by citations
- Media Technology — 19 citations into it
- Model Architectures — 12 citations into it
- Optimization & Training — 12 citations into it
- Computer Graphics and Computer-Aided Design — 9 citations into it
Whom Junge Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Ross B. Girshick
- Geoffrey E. Hinton
- Alex Krizhevsky
- Diederik P. Kingma
- Yann LeCun
- Yoshua Bengio
- Ilya Sutskever
- Andrew Zisserman
- Pedro F. Felzenszwalb
Who trusts Junge Zhang overall
- Zhanchao Huang
- Yali Li
- Xiaoyu Wang
- Lichao Huang
- Fahad Shahbaz Khan
- Xiaoyuan Yu
- Suo Qiu
- Jianlin Wang
- Jasper R. R. Uijlings
- Yongjun Hong
Papers from Junge Zhang's perspective
Ordered by how strongly the researchers Junge Zhang trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Boosted local structured HOG-LBP for object localization (2011) — 170 citations
- Fast End-to-End Trainable Guided Filter (2018) — 266 citations
- GP-GAN: Towards Realistic High-Resolution Image Blending (2017) — 282 citations
- Few-Shot Image Recognition With Knowledge Transfer (2019) — 232 citations
- Large-Scale Weakly Supervised Object Localization via Latent Category Learning (2015) — 64 citations
- FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation (2019) — 340 citations
- Robust view transformation model for gait recognition (2011) — 383 citations