Guilin Liu
Computer Vision and Pattern Recognition · with Catanzaro · 2018–2023
A researcher in the Science corpus: 8 papers; trusts 1,002 researchers and is trusted by 43 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 413 citations into it; #4,864 of 21,575 by trust here, #2,605 by citations
- Generative Models — 166 citations into it; #1,956 of 1,956 by trust here, #616 by citations
- Artificial Intelligence — 125 citations into it
- Computer Graphics and Computer-Aided Design — 38 citations into it
- Model Architectures — 34 citations into it
- Media Technology — 29 citations into it
- Optimization & Training — 22 citations into it
- 3D Vision & Pose — 11 citations into it
Whom Guilin Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Diederik P. Kingma
- Alex Krizhevsky
- Karen Simonyan
- Ross B. Girshick
- Yann LeCun
- Yoshua Bengio
- Ilya Sutskever
- Andrew Zisserman
Who trusts Guilin Liu overall
- Yanhong Zeng
- Håkon Hukkelås
- Jianlong Fu
- Yuqing Ma
- Bilal Alsallakh
- Youngjoo Jo
- C. Belthangady
- Rameen Abdal
- Mark Sabini
- Hongyu Liu
Papers from Guilin Liu's perspective
Ordered by how strongly the researchers Guilin Liu trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- 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
- Going deeper with convolutions
Their papers
- Video-to-Video Synthesis (2018) — 1,093 citations
- Image Inpainting for Irregular Holes Using Partial Convolutions (2018) — 2,284 citations
- Few-shot Video-to-Video Synthesis (2019) — 402 citations
- Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models (2023) — 326 citations
- DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision (2021) — 96 citations
- Neural Inverse Rendering of an Indoor Scene From a Single Image (2019) — 178 citations
- Dual Contrastive Loss and Attention for GANs (2021) — 70 citations
- Partial Convolution based Padding (2018) — 101 citations