José Lezama

Computer Vision and Pattern Recognition · 2017–2023

A researcher in the Science corpus: 7 papers; trusts 660 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 326 citations into it
• Generative Models — 175 citations into it
• Artificial Intelligence — 154 citations into it
• Multimodal Learning — 55 citations into it
• Model Architectures — 42 citations into it
• Signal Processing — 37 citations into it
• Computer Graphics and Computer-Aided Design — 28 citations into it
• Representation & Self-Supervised Learning — 27 citations into it

Whom José Lezama trusts overall

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

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

Who trusts José Lezama overall

1. Bingyi Zhang
2. Lijun Yu
3. Agrim Gupta

Papers from José Lezama's perspective

Ordered by how strongly the researchers José Lezama 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. Attention is All you Need (Neural Information Processing Systems)
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. Learning Multiple Layers of Features from Tiny Images

Their papers

• Muse: Text-To-Image Generation via Masked Generative Transformers (2023) — 783 citations
• MAGVIT: Masked Generative Video Transformer (2022) — 394 citations
• Improved Masked Image Generation with Token-Critic (2022) — 74 citations
• Photorealistic Video Generation with Diffusion Models (2023) — 341 citations
• Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation (2023) — 665 citations
• VideoPoet: A Large Language Model for Zero-Shot Video Generation (2023) — 521 citations
• OLE: Orthogonal Low-rank Embedding, A Plug and Play Geometric Loss for Deep Learning (2017) — 88 citations