Yong Zhang

Computer Vision and Pattern Recognition · 2020–2024

A researcher in the Science corpus: 10 papers; trusts 617 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 306 citations into it
• Artificial Intelligence — 140 citations into it
• Generative Models — 131 citations into it
• Multimodal Learning — 52 citations into it
• Computer Graphics and Computer-Aided Design — 40 citations into it
• Optimization & Training — 34 citations into it
• Federated & Distributed Learning — 33 citations into it
• Statistical and Nonlinear Physics — 29 citations into it

Whom Yong Zhang trusts overall

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

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

Who trusts Yong Zhang overall

1. Kepan Nan
2. Yaofang Liu

Papers from Yong Zhang's perspective

Ordered by how strongly the researchers Yong Zhang 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. GENERATIVE ADVERSARIAL NETS

Their papers

• EvalCrafter: Benchmarking and Evaluating Large Video Generation Models (2023) — 347 citations
• FateZero: Fusing Attentions for Zero-shot Text-based Video Editing (2023) — 548 citations
• VideoCrafter1: Open Diffusion Models for High-Quality Video Generation (2023) — 596 citations
• VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models (2024) — 654 citations
• DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors (2023) — 507 citations
• Generating Human Motion from Textual Descriptions with Discrete Representations (2023) — 716 citations
• SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation (2022) — 493 citations
• Latent Video Diffusion Models for High-Fidelity Long Video Generation (2022) — 429 citations
• Personalized Cross-Silo Federated Learning on Non-IID Data (2020) — 856 citations
• Personalized Federated Learning: An Attentive Collaboration Approach (2020) — 29 citations