Xavier Puig

Computer Vision and Pattern Recognition · 2016–2022

A researcher in the Science corpus: 7 papers; trusts 649 researchers and is trusted by 1,598 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 160 citations into it; #1,029 of 21,575 by trust here, #1,157 by citations
• Artificial Intelligence — 128 citations into it; #17,743 of 35,345 by trust here, #6,193 by citations
• Reinforcement Learning — 52 citations into it; #1,539 of 2,242 by trust here, #700 by citations
• Natural Language Processing — 48 citations into it
• Evaluation & Benchmarks — 35 citations into it; #388 of 3,147 by trust here, #264 by citations
• Model Architectures — 23 citations into it
• Aerospace Engineering — 13 citations into it
• Social Psychology — 7 citations into it

Whom Xavier Puig trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ilya Sutskever
5. Yoshua Bengio
6. Diederik P. Kingma
7. Ross B. Girshick
8. Yann LeCun
9. Sepp Hochreiter
10. Antonio Torralba

Who trusts Xavier Puig overall

1. Xiaodan Liang
2. Zirui Zhao
3. Chuang Gan
4. Bolei Zhou
5. Antonio Torralba
6. Jianwei Yang
7. Shuang Li
8. Yuhui Yuan
9. Liang-Chieh Chen
10. Golnaz Ghiasi

Papers from Xavier Puig's perspective

Ordered by how strongly the researchers Xavier Puig 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. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
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

• Scene Parsing through ADE20K Dataset (2017) — 3,986 citations
• Semantic Understanding of Scenes Through the ADE20K Dataset (2016) — 2,400 citations
• VirtualHome: Simulating Household Activities Via Programs (2018) — 691 citations
• Open Vocabulary Scene Parsing (2017) — 144 citations
• Pre-Trained Language Models for Interactive Decision-Making (2022) — 334 citations
• Synthesizing Environment-Aware Activities via Activity Sketches (2019) — 44 citations
• Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration (2020) — 185 citations