Jun Jin

Computer Vision and Pattern Recognition · 2018–2023

A researcher in the Science corpus: 2 papers; trusts 74 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 44 citations into it
• Artificial Intelligence — 38 citations into it
• Model Architectures — 5 citations into it

Whom Jun Jin trusts overall

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

1. Kaiming He
2. Karen Simonyan
3. Jia Deng
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Andrew Zisserman
7. Oussama Khatib
8. Ross B. Girshick
9. Shaoqing Ren
10. X. Zhang

Who trusts Jun Jin overall

1. Ali Ayub

Papers from Jun Jin's perspective

Ordered by how strongly the researchers Jun Jin 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. ImageNet: A large-scale hierarchical image database
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Long Short-Term Memory
9. Microsoft COCO: Common Objects in Context
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• EmbodiedGPT: Vision-Language Pre-Training via Embodied Chain of Thought (2023) — 430 citations
• Online Object and Task Learning via Human Robot Interaction (2018) — 33 citations