Mulin Yu

Computer Vision and Pattern Recognition · 2023–2024

A researcher in the Science corpus: 2 papers; trusts 58 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 70 citations into it
• Computer Graphics and Computer-Aided Design — 60 citations into it
• Computational Mechanics — 46 citations into it
• 3D Vision & Pose — 11 citations into it
• Aerospace Engineering — 6 citations into it

Whom Mulin Yu trusts overall

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

1. Jonathan T. Barron
2. Johannes L. Schönberger
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. Kaiming He
6. Alex Krizhevsky
7. Bernhard Kerbl
8. Zhou Wang
9. Jitendra Malik
10. Ben Mildenhall

Papers from Mulin Yu's perspective

Ordered by how strongly the researchers Mulin Yu 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. 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. GENERATIVE ADVERSARIAL NETS

Their papers

• Octree-GS: Towards Consistent Real-time Rendering with LOD-Structured 3D Gaussians (2024) — 300 citations
• Scaffold-GS: Structured 3D Gaussians for View-Adaptive Rendering (2023) — 863 citations