Arjun Majumdar

Computer Vision and Pattern Recognition · 2018–2024

A researcher in the Science corpus: 6 papers; trusts 559 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 175 citations into it; #6,210 of 21,575 by trust here, #5,620 by citations
• Artificial Intelligence — 144 citations into it; #10,953 of 35,345 by trust here, #7,413 by citations
• Multimodal Learning — 55 citations into it; #854 of 1,211 by trust here, #736 by citations
• Natural Language Processing — 27 citations into it; #4,311 of 5,688 by trust here, #2,846 by citations
• Aerospace Engineering — 25 citations into it
• Evaluation & Benchmarks — 23 citations into it
• Robotics & Control — 22 citations into it
• Model Architectures — 12 citations into it

Whom Arjun Majumdar trusts overall

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

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

Who trusts Arjun Majumdar overall

1. Yicong Hong
2. Gengze Zhou
3. Qi Wu
4. Alexander Pashevich
5. Shizhe Chen
6. S. Gadre
7. Cordelia Schmid
8. Naoki Yokoyama
9. Alessandro Suglia
10. Salman Hameed Khan

Papers from Arjun Majumdar's perspective

Ordered by how strongly the researchers Arjun Majumdar 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning (2018) — 224 citations
• Beyond the Nav-Graph: Vision-and-Language Navigation in Continuous Environments (2020) — 578 citations
• Improving Vision-and-Language Navigation with Image-Text Pairs from the Web (2020) — 277 citations
• Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence? (2023) — 303 citations
• ZSON: Zero-Shot Object-Goal Navigation using Multimodal Goal Embeddings (2022) — 316 citations
• OpenEQA: Embodied Question Answering in the Era of Foundation Models (2024) — 348 citations