Aarush Katta

Computer Vision and Pattern Recognition · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 73 citations into it; #21,283 of 21,575 by trust here, #2,091 by citations

Whom Aarush Katta trusts

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

1. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
2. Kaiming He (in Computer Vision and Pattern Recognition)
3. Ilya Sutskever (in Computer Vision and Pattern Recognition)
4. Li Fei-Fei (in Computer Vision and Pattern Recognition)
5. Ross B. Girshick (in Computer Vision and Pattern Recognition)
6. Andrew Zisserman (in Computer Vision and Pattern Recognition)
7. Shaoqing Ren (in Computer Vision and Pattern Recognition)
8. Jitendra Malik (in Computer Vision and Pattern Recognition)
9. Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)
10. Karen Simonyan (in Computer Vision and Pattern Recognition)

Who trusts Aarush Katta

1. Srivatsa Kundurthy (in Computer Vision and Pattern Recognition)

Papers from Aarush Katta's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. ImageNet: A large-scale hierarchical image database
3. ImageNet Large Scale Visual Recognition Challenge
4. Microsoft COCO: Common Objects in Context
5. Language Models are Few-Shot Learners (Neural Information Processing Systems)
6. ImageNet classification with deep convolutional neural networks
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (International Conference on Learning Representations)
9. Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
10. Learning Transferable Visual Models From Natural Language Supervision (International Conference on Machine Learning)

Their papers

• LAION-5B: An open large-scale dataset for training next generation image-text models (2022) — 5,389 citations
• LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs (2021) — 1,887 citations