Minjie Cai

Computer Vision and Pattern Recognition · 2016–2020

A researcher in the Science corpus: 2 papers; trusts 301 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 42 citations into it; #17,617 of 21,575 by trust here, #14,151 by citations
• Artificial Intelligence — 32 citations into it; #29,086 of 35,345 by trust here, #33,294 by citations
• Human-Computer Interaction — 10 citations into it; #1,646 of 2,253 by trust here, #1,127 by citations
• Representation & Self-Supervised Learning — 9 citations into it; #2,663 of 3,145 by trust here, #3,089 by citations
• Probabilistic & Bayesian Methods — 7 citations into it

Whom Minjie Cai trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Diederik P. Kingma
4. Cheng Li
5. Radford M. Neal
6. Ilya Sutskever
7. Kaiming He
8. Yoshua Bengio
9. Yann LeCun
10. Ross B. Girshick

Who trusts Minjie Cai overall

1. Fanqing Lin
2. Lingzhi Zhang
3. Guillermo Garcia-Hernando
4. Tony R. Martinez
5. Moloud Abdar
6. Francesco Ragusa
7. Shenghao Zhou
8. Shanxin Yuan
9. Antonino Furnari
10. Kyungjun Lee

Papers from Minjie Cai's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Understanding Hand-Object Manipulation with Grasp Types and Object Attributes (2016) — 94 citations
• Generalizing Hand Segmentation in Egocentric Videos With Uncertainty-Guided Model Adaptation (2020) — 47 citations