Yong Zhang

Computer Vision and Pattern Recognition · with Fan · 2019–2023

A researcher in the Science corpus: 6 papers; trusts 576 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 169 citations into it
• Artificial Intelligence — 80 citations into it
• Generative Models — 50 citations into it
• Safety, Robustness & Interpretability — 27 citations into it
• Evaluation & Benchmarks — 20 citations into it
• Optimization & Training — 15 citations into it
• Model Architectures — 12 citations into it
• Signal Processing — 12 citations into it

Whom Yong Zhang trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Alex Krizhevsky
4. Kaiming He
5. Yoshua Bengio
6. Yann LeCun
7. Christian Szegedy
8. Jimmy Ba
9. Ross B. Girshick
10. Ilya Sutskever

Who trusts Yong Zhang overall

1. Yuval Alaluf
2. Gwanghyun Kim
3. Wenhu Chen
4. Guillaume Couairon

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. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• High-Fidelity GAN Inversion for Image Attribute Editing (2021) — 305 citations
• Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning (2019) — 95 citations
• Exact Adversarial Attack to Image Captioning via Structured Output Learning With Latent Variables (2019) — 61 citations
• Sparse Adversarial Attack via Perturbation Factorization (2020) — 98 citations
• UCF: Uncovering Common Features for Generalizable Deepfake Detection (2023) — 302 citations
• DAE-GAN: Dynamic Aspect-aware GAN for Text-to-Image Synthesis (2021) — 128 citations