Zehuan Yuan

Computer Vision and Pattern Recognition · 2020–2024

A researcher in the Science corpus: 10 papers; trusts 1,119 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 428 citations into it; #12,855 of 21,575 by trust here, #4,807 by citations
• Artificial Intelligence — 254 citations into it
• Generative Models — 74 citations into it
• Large Language Models — 60 citations into it
• Model Architectures — 57 citations into it
• Evaluation & Benchmarks — 45 citations into it
• Representation & Self-Supervised Learning — 28 citations into it
• Optimization & Training — 22 citations into it

Whom Zehuan Yuan trusts overall

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

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

Who trusts Zehuan Yuan overall

1. Jinkun Cao

Papers from Zehuan Yuan's perspective

Ordered by how strongly the researchers Zehuan Yuan 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Sparse R-CNN: End-to-End Object Detection with Learnable Proposals (2020) — 1,499 citations
• TransTrack: Multiple-Object Tracking with Transformer (2020) — 798 citations
• ByteTrack: Multi-Object Tracking by Associating Every Detection Box (2021) — 2,498 citations
• Language as Queries for Referring Video Object Segmentation (2022) — 263 citations
• DanceTrack: Multi-Object Tracking in Uniform Appearance and Diverse Motion (2021) — 422 citations
• Infinity∞: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis (2024) — 299 citations
• Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction (2024) — 1,081 citations
• Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation (2024) — 767 citations
• Exploring Balanced Feature Spaces for Representation Learning (2021) — 303 citations
• Focal and Global Knowledge Distillation for Detectors (2021) — 385 citations