Yanwei Li

Computer Vision and Pattern Recognition · Neural Information Processing Systems · 2018–2023

A researcher in the Science corpus: 8 papers; trusts 1,034 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 355 citations into it; #9,855 of 21,575 by trust here, #4,955 by citations
• Artificial Intelligence — 173 citations into it
• Aerospace Engineering — 55 citations into it
• Model Architectures — 50 citations into it
• Evaluation & Benchmarks — 29 citations into it
• Computational Mechanics — 20 citations into it
• Geology — 16 citations into it
• Optimization & Training — 15 citations into it

Whom Yanwei Li trusts overall

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

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

Who trusts Yanwei Li overall

1. Zhiqi Li
2. Huiyu Wang
3. Qihang Yu
4. Wenhai Wang
5. Liang-Chieh Chen
6. Xiaojuan Qi
7. Rohit Mohan
8. Wenwei Zhang
9. Siyuan Qiao
10. Zheng Ding

Papers from Yanwei Li's perspective

Ordered by how strongly the researchers Yanwei Li 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Attention-Guided Unified Network for Panoptic Segmentation (2018) — 293 citations
• Fully Convolutional Networks for Panoptic Segmentation (2020) — 199 citations
• LISA: Reasoning Segmentation via Large Language Model (2023) — 972 citations
• Learning Dynamic Routing for Semantic Segmentation (2020) — 189 citations
• GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction (2023) — 329 citations
• Focal Sparse Convolutional Networks for 3D Object Detection (2022) — 313 citations
• Fully Convolutional Networks for Panoptic Segmentation With Point-Based Supervision (2021) — 65 citations
• Unifying Voxel-based Representation with Transformer for 3D Object Detection (2022) — 391 citations