Ruilong Li
Computer Vision and Pattern Recognition · IEEE International Conference on Computer Vision · 2021–2024
A researcher in the Science corpus: 4 papers; trusts 152 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 112 citations into it; #14,159 of 21,575 by trust here, #6,542 by citations
- Computer Graphics and Computer-Aided Design — 58 citations into it; #1,355 of 1,584 by trust here, #411 by citations
- Computational Mechanics — 44 citations into it; #8,861 of 10,001 by trust here, #1,778 by citations
- 3D Vision & Pose — 27 citations into it
- Artificial Intelligence — 18 citations into it
- Control and Systems Engineering — 14 citations into it; #6,316 of 8,257 by trust here, #4,262 by citations
Whom Ruilong Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Jimmy Ba
- Alex Krizhevsky
- Yoshua Bengio
- Kaiming He
- Yann LeCun
- Ilya Sutskever
- Ross B. Girshick
- Karen Simonyan
Who trusts Ruilong Li overall
- Mathis Petrovich
- Guy Tevet
- Jo-Han Tseng
- Ye Yuan
- Shao-Wei Liu
- Anpei Chen
- Michael J. Black
- Antoine Guédon
- Zehao Yu
- Ang Cao
Papers from Ruilong Li's perspective
Ordered by how strongly the researchers Ruilong Li trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- PlenOctrees for Real-time Rendering of Neural Radiance Fields (2021) — 1,321 citations
- AI Choreographer: Music Conditioned 3D Dance Generation with AIST++ (2021) — 734 citations
- Nerfstudio: A Modular Framework for Neural Radiance Field Development (2023) — 995 citations
- gsplat: An Open-Source Library for Gaussian Splatting (2024) — 330 citations