Santhosh K. Ramakrishnan
Computer Vision and Pattern Recognition · 2018–2023
A researcher in the Science corpus: 7 papers; trusts 866 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 419 citations into it; #8,479 of 21,575 by trust here, #5,053 by citations
- Artificial Intelligence — 196 citations into it; #22,904 of 35,345 by trust here, #28,481 by citations
- Aerospace Engineering — 87 citations into it; #4,793 of 6,421 by trust here, #2,734 by citations
- Reinforcement Learning — 87 citations into it; #1,889 of 2,242 by trust here, #1,999 by citations
- Evaluation & Benchmarks — 83 citations into it
- Control and Systems Engineering — 48 citations into it
- Robotics & Control — 43 citations into it; #434 of 609 by trust here, #546 by citations
- 3D Vision & Pose — 34 citations into it
Whom Santhosh K. Ramakrishnan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Kaiming He
- Alex Krizhevsky
- Richard S. Sutton
- Yoshua Bengio
- Yann LeCun
- Ross B. Girshick
- Ronald J. Williams
- Ilya Sutskever
Who trusts Santhosh K. Ramakrishnan overall
- Kristen Grauman
- Tushar Nagarajan
- Jiafei Duan
- Ziad Al-Halah
- Peter Karkus
- Dinesh Jayaraman
- Arjun Majumdar
- Siyuan Huang
- Samson Yu
- Matt Deitke
Papers from Santhosh K. Ramakrishnan's perspective
Ordered by how strongly the researchers Santhosh K. Ramakrishnan trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Ego4D: Around the World in 3,000 Hours of Egocentric Video (2021) — 1,925 citations
- Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI (2021) — 764 citations
- An Exploration of Embodied Visual Exploration (2020) — 113 citations
- Sidekick Policy Learning for Active Visual Exploration (2018) — 30 citations
- Occupancy Anticipation for Efficient Exploration and Navigation (2020) — 204 citations
- Emergence of exploratory look-around behaviors through active observation completion (2019) — 46 citations
- Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives (2023) — 529 citations