Eric Chan

Computer Vision and Pattern Recognition · 2011–2023

A researcher in the Science corpus: 6 papers; trusts 379 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 259 citations into it; #21,523 of 21,575 by trust here, #4,690 by citations
• Computer Graphics and Computer-Aided Design — 140 citations into it; #1,167 of 1,584 by trust here, #153 by citations
• Computational Mechanics — 113 citations into it
• Generative Models — 101 citations into it
• 3D Vision & Pose — 71 citations into it
• Artificial Intelligence — 47 citations into it
• Statistical and Nonlinear Physics — 21 citations into it
• Evaluation & Benchmarks — 12 citations into it

Whom Eric Chan trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Kaiming He
4. Alex Krizhevsky
5. Tero Karras
6. Yoshua Bengio
7. Yann LeCun
8. Ilya Sutskever
9. Michael Niemeyer
10. Ross B. Girshick

Who trusts Eric Chan overall

1. Peng Wang
2. Haochen Wang
3. Vincent Sitzmann
4. Ang Cao
5. Jun Gao
6. Tengfei Wang
7. Yinghao Xu
8. Yichun Shi
9. Stanislaw Szymanowicz
10. Jonathan T. Barron

Papers from Eric Chan's perspective

Ordered by how strongly the researchers Eric Chan 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. GENERATIVE ADVERSARIAL NETS

Their papers

• pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis (2020) — 978 citations
• Efficient Geometry-aware 3D Generative Adversarial Networks (2021) — 1,520 citations
• Generative Novel View Synthesis with 3D-Aware Diffusion Models (2023) — 328 citations
• 3D Neural Field Generation Using Triplane Diffusion (2022) — 336 citations
• MetaSDF: Meta-learning Signed Distance Functions (2020) — 295 citations
• Learning photographic global tonal adjustment with a database of input/output image pairs (2011)