Shanghang Zhang

Computer Vision and Pattern Recognition · with Keutzer · 2023–2024

A researcher in the Science corpus: 2 papers; trusts 23 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 72 citations into it
• Generative Models — 30 citations into it

Whom Shanghang Zhang trusts overall

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

1. Alex Krizhevsky

Papers from Shanghang Zhang's perspective

Ordered by how strongly the researchers Shanghang Zhang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Learning Multiple Layers of Features from Tiny Images
2. GENERATIVE ADVERSARIAL NETS
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Improved Techniques for Training GANs
6. Attention is All you Need (Neural Information Processing Systems)
7. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
8. ImageNet: A large-scale hierarchical image database
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Gradient-based learning applied to document recognition

Their papers

• SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference (2024) — 373 citations
• Q-Diffusion: Quantizing Diffusion Models (2023) — 316 citations