Ceyuan Yang

Computer Vision and Pattern Recognition · 2018–2024

A researcher in the Science corpus: 12 papers; trusts 1,491 researchers and is trusted by 39 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 541 citations into it; #4,729 of 21,575 by trust here, #3,810 by citations
• Generative Models — 193 citations into it; #759 of 1,956 by trust here, #909 by citations
• Artificial Intelligence — 192 citations into it; #35,096 of 35,345 by trust here, #17,776 by citations
• Representation & Self-Supervised Learning — 100 citations into it
• Computer Graphics and Computer-Aided Design — 83 citations into it
• Media Technology — 50 citations into it; #3,208 of 3,621 by trust here, #2,033 by citations
• Multimodal Learning — 39 citations into it
• Computational Mechanics — 35 citations into it

Whom Ceyuan Yang trusts overall

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

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

Who trusts Ceyuan Yang overall

1. Yinghao Xu
2. Zongze Wu
3. Yujun Shen
4. Gong Cheng
5. Christoph Feichtenhofer
6. Jiapeng Zhu
7. Zhendong Wang
8. Jonathan C. Stroud
9. Tianjian Meng
10. Hanwen Liang

Papers from Ceyuan Yang's perspective

Ordered by how strongly the researchers Ceyuan Yang 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. 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. Going deeper with convolutions

Their papers

• InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs (2020) — 709 citations
• Video Representation Learning with Visual Tempo Consistency (2020) — 94 citations
• Generative Hierarchical Features from Synthesizing Images (2020) — 126 citations
• AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning (2023) — 1,619 citations
• Adapting Object Detectors via Selective Cross-Domain Alignment (2019) — 378 citations
• Temporal Pyramid Network for Action Recognition (2020) — 445 citations
• LaVie: High-Quality Video Generation with Cascaded Latent Diffusion Models (2023) — 404 citations
• Data-Efficient Instance Generation from Instance Discrimination (2021) — 97 citations
• One-Shot Generative Domain Adaptation (2021) — 69 citations
• CameraCtrl: Enabling Camera Control for Text-to-Video Generation (2024) — 425 citations
• GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation (2024) — 333 citations
• When Deep Learning Meets Metric Learning: Remote Sensing Image Scene Classification via Learning Discriminative CNNs (2018) — 1,041 citations