Kenneth Marino

Computer Vision and Pattern Recognition · 2016–2023

A researcher in the Science corpus: 6 papers; trusts 1,037 researchers and is trusted by 369 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 224 citations into it; #2,160 of 21,575 by trust here, #2,381 by citations
• Artificial Intelligence — 199 citations into it; #7,580 of 35,345 by trust here, #3,907 by citations
• Multimodal Learning — 81 citations into it
• Natural Language Processing — 64 citations into it
• Evaluation & Benchmarks — 36 citations into it
• Graph Learning — 24 citations into it; #350 of 693 by trust here, #392 by citations
• Generative Models — 21 citations into it
• Representation & Self-Supervised Learning — 17 citations into it

Whom Kenneth Marino trusts overall

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

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

Who trusts Kenneth Marino overall

1. X. Wang
2. Weizhe Lin
3. Zhengyuan Yang
4. Haotian Liu
5. Abhinav Kumar Gupta
6. Bo Li
7. Man Luo
8. Dustin Schwenk
9. Tianshui Chen
10. Prajwal Gatti

Papers from Kenneth Marino's perspective

Ordered by how strongly the researchers Kenneth Marino 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. 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

• OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge (2019) — 1,612 citations
• The Pose Knows: Video Forecasting by Generating Pose Futures (2017) — 359 citations
• A-OKVQA: A Benchmark for Visual Question Answering using World Knowledge (2022) — 950 citations
• The More You Know: Using Knowledge Graphs for Image Classification (2016) — 379 citations
• KRISP: Integrating Implicit and Symbolic Knowledge for Open-Domain Knowledge-Based VQA (2020) — 247 citations
• Collaborating with language models for embodied reasoning (2023) — 91 citations