Jianbo Jiao

Computer Vision and Pattern Recognition · 2017–2023

A researcher in the Science corpus: 5 papers; trusts 812 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 169 citations into it; #14,395 of 21,575 by trust here, #9,187 by citations
• Artificial Intelligence — 120 citations into it; #34,152 of 35,345 by trust here, #28,481 by citations
• Representation & Self-Supervised Learning — 57 citations into it
• Meta & Continual Learning — 29 citations into it
• Evaluation & Benchmarks — 19 citations into it
• Model Architectures — 16 citations into it
• Human-Computer Interaction — 9 citations into it
• Optimization & Training — 9 citations into it

Whom Jianbo Jiao 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. Andrew Zisserman
6. Karen Simonyan
7. Yoshua Bengio
8. Yann LeCun
9. Diederik P. Kingma
10. Ilya Sutskever

Who trusts Jianbo Jiao overall

1. Senthil Purushwalkam
2. Tianhao Li
3. Pritam Sarkar
4. Hanwen Liang
5. Gengwei Zhang
6. Jie Gui

Papers from Jianbo Jiao's perspective

Ordered by how strongly the researchers Jianbo Jiao 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. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
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

• Self-Supervised Spatio-Temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics (2019) — 223 citations
• Self-supervised Video Representation Learning by Pace Prediction (2020) — 263 citations
• A hand pose tracking benchmark from stereo matching (2017) — 98 citations
• CoinSeg: Contrast Inter- and Intra- Class Representations for Incremental Segmentation (2023) — 37 citations
• Mining Unseen Classes via Regional Objectness: A Simple Baseline for Incremental Segmentation (2022) — 51 citations