Xiao Wang

Computer Vision and Pattern Recognition · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2018–2023

A researcher in the Science corpus: 5 papers; trusts 921 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 251 citations into it
• Artificial Intelligence — 199 citations into it
• Multimodal Learning — 87 citations into it
• Representation & Self-Supervised Learning — 71 citations into it
• Evaluation & Benchmarks — 37 citations into it
• Model Architectures — 24 citations into it
• Optimization & Training — 16 citations into it
• Generative Models — 11 citations into it

Whom Xiao Wang trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Yoshua Bengio
6. Yann LeCun
7. Ross B. Girshick
8. Ilya Sutskever
9. Karen Simonyan
10. L. Eon Bottou

Who trusts Xiao Wang overall

1. Meixin Zhu
2. Botao Ye
3. Liting Lin
4. Xin Chen
5. M. Alam
6. Yaozong Zheng
7. Yuxuan Li
8. Boyu Chen

Papers from Xiao Wang's perspective

Ordered by how strongly the researchers Xiao Wang 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. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
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

• Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark (2021) — 297 citations
• Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment (2021) — 103 citations
• Large-scale Multi-modal Pre-trained Models: A Comprehensive Survey (2023) — 326 citations
• Contrastive Learning With Stronger Augmentations (2021) — 326 citations
• Capturing Car-Following Behaviors by Deep Learning (2018) — 308 citations