Zhengkai Jiang
Computer Vision and Pattern Recognition · 2018–2023
A researcher in the Science corpus: 4 papers; trusts 427 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 129 citations into it; #9,316 of 21,575 by trust here, #5,890 by citations
- Artificial Intelligence — 80 citations into it; #35,001 of 35,345 by trust here, #11,750 by citations
- Model Architectures — 22 citations into it
- Aerospace Engineering — 16 citations into it
- Natural Language Processing — 14 citations into it
- Computational Mechanics — 10 citations into it; #4,637 of 10,001 by trust here, #3,559 by citations
- Optimization & Training — 10 citations into it
- Evaluation & Benchmarks — 9 citations into it
Whom Zhengkai Jiang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Diederik P. Kingma
- Ross B. Girshick
- Alex Krizhevsky
- Yoshua Bengio
- Karen Simonyan
- Yann LeCun
- Christian Szegedy
- Ilya Sutskever
Who trusts Zhengkai Jiang overall
- Junjie Huang
- Peng Gao
- Tianwei Yin
- Yingfei Liu
- Renrui Zhang
- Xingyi Zhou
- Dalu Guo
- Guan Huang
- Pan Lu
- Yue Wang
Papers from Zhengkai Jiang's perspective
Ordered by how strongly the researchers Zhengkai Jiang 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)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- 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
- Dynamic Fusion With Intra- and Inter-Modality Attention Flow for Visual Question Answering (2018) — 416 citations
- Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection (2019) — 587 citations
- Personalize Segment Anything Model with One Shot (2023) — 372 citations
- Rethinking Counting and Localization in Crowds: A Purely Point-Based Framework (2021) — 403 citations