Tai Wang

Computer Vision and Pattern Recognition · 2020–2023

A researcher in the Science corpus: 4 papers; trusts 548 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 150 citations into it; #6,482 of 21,575 by trust here, #8,021 by citations
• Artificial Intelligence — 57 citations into it
• Aerospace Engineering — 49 citations into it; #2,780 of 6,421 by trust here, #2,367 by citations
• Computational Mechanics — 30 citations into it
• Geology — 13 citations into it
• Environmental Engineering — 12 citations into it
• Evaluation & Benchmarks — 10 citations into it
• Model Architectures — 10 citations into it

Whom Tai Wang trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Shaoqing Ren
6. Tsung-Yi Lin
7. Yoshua Bengio
8. Diederik P. Kingma
9. Yann LeCun
10. Jia Deng

Who trusts Tai Wang overall

1. Junjie Huang
2. Yingfei Liu
3. Yi Wei
4. Guan Huang
5. Yinhao Li
6. Tingting Liang
7. Yue Wang
8. Tiancai Wang
9. Wenzhao Zheng
10. Xuanyao Chen

Papers from Tai Wang's perspective

Ordered by how strongly the researchers Tai 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. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detection (2021) — 814 citations
• Probabilistic and Geometric Depth: Detecting Objects in Perspective (2021) — 366 citations
• Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation (2020) — 723 citations
• PointLLM: Empowering Large Language Models to Understand Point Clouds (2023) — 396 citations