Zisheng Cao
Computer Vision and Pattern Recognition · 2019–2020
A researcher in the Science corpus: 2 papers; trusts 229 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 67 citations into it; #21,138 of 21,575 by trust here, #11,721 by citations
- Media Technology — 28 citations into it; #3,549 of 3,621 by trust here, #1,598 by citations
- Generative Models — 11 citations into it; #1,929 of 1,956 by trust here, #1,415 by citations
- Artificial Intelligence — 9 citations into it
- Evaluation & Benchmarks — 5 citations into it; #3,086 of 3,147 by trust here, #2,330 by citations
Whom Zisheng Cao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yoshua Bengio
- David G. Lowe
- Jimmy Ba
- Ilya Sutskever
- Yann LeCun
- Ross B. Girshick
Who trusts Zisheng Cao overall
Papers from Zisheng Cao's perspective
Ordered by how strongly the researchers Zisheng Cao 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- GENERATIVE ADVERSARIAL NETS
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Toward Real-World Single Image Super-Resolution: A New Benchmark and a New Model (2019) — 752 citations
- Learning Image-Adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-Time (2020) — 363 citations