Jing Jin

Computer Vision and Pattern Recognition · with Hu · 2021

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 15 citations into it

Whom Jing Jin trusts overall

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

1. Kaiming He

Papers from Jing Jin's perspective

Ordered by how strongly the researchers Jing 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. Microsoft COCO: Common Objects in Context
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Show and tell: A neural image caption generator
8. Attention is All you Need (Neural Information Processing Systems)
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Extracting and composing robust features with denoising autoencoders

Their papers

• DSSL: Deep Surroundings-person Separation Learning for Text-based Person Retrieval (2021) — 314 citations