Yael Pritch

Computer Vision and Pattern Recognition · 2001–2022

A researcher in the Science corpus: 6 papers; trusts 276 researchers and is trusted by 383 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 166 citations into it; #2,103 of 21,575 by trust here, #2,949 by citations
• Generative Models — 85 citations into it; #877 of 1,956 by trust here, #377 by citations
• Multimodal Learning — 39 citations into it; #516 of 1,211 by trust here, #305 by citations
• Computer Graphics and Computer-Aided Design — 28 citations into it; #1,043 of 1,584 by trust here, #212 by citations
• Statistical and Nonlinear Physics — 9 citations into it
• Biophysics — 8 citations into it
• Cognitive Neuroscience — 7 citations into it

Whom Yael Pritch trusts overall

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

1. Yuri Boykov
2. Vladimir Kolmogorov
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Alex Krizhevsky
6. Kaiming He
7. Antonio Criminisi
8. Lior Wolf
9. Yoshua Bengio
10. Ramin Zabih

Who trusts Yael Pritch overall

1. Jia-Bin Huang
2. Kaiming He
3. Wenguan Wang
4. Guanbin Li
5. Christine M. Guillemot
6. Johannes Peter Kopf
7. Chen Gao
8. Ming-Ming Cheng
9. Meng-Li Shih
10. Deng-Ping Fan

Papers from Yael Pritch's perspective

Ordered by how strongly the researchers Yael Pritch 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. GENERATIVE ADVERSARIAL NETS
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation (2022) — 4,398 citations
• Saliency filters: Contrast based filtering for salient region detection (2012) — 2,181 citations
• Shift-map image editing (2009) — 451 citations
• Scene reconstruction from high spatio-angular resolution light fields (2013) — 473 citations
• Prompt-to-Prompt Image Editing with Cross Attention Control (2022) — 2,848 citations
• Omnistereo: Panoramic Stereo Imaging (2001) — 302 citations