Santosh Kumar Divvala
Computer Vision and Pattern Recognition · 2009–2019
A researcher in the Science corpus: 7 papers; trusts 1,302 researchers and is trusted by 4,348 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 233 citations into it; #488 of 21,575 by trust here, #512 by citations
- Artificial Intelligence — 118 citations into it; #5,778 of 35,345 by trust here, #6,911 by citations
- Evaluation & Benchmarks — 27 citations into it
- Natural Language Processing — 22 citations into it; #4,503 of 5,688 by trust here, #3,574 by citations
- Model Architectures — 16 citations into it
- Media Technology — 15 citations into it
- Representation & Self-Supervised Learning — 13 citations into it
- Aerospace Engineering — 12 citations into it
Whom Santosh Kumar Divvala trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ross B. Girshick
- Geoffrey E. Hinton
- Alex Krizhevsky
- Antonio Torralba
- Kaiming He
- Andrew Zisserman
- Karen Simonyan
- Diederik P. Kingma
- David G. Lowe
- Yoshua Bengio
Who trusts Santosh Kumar Divvala overall
- Li Fei-Fei
- Abhinav Kumar Gupta
- Xinlei Chen
- Wanli Ouyang
- Xiaogang Wang
- Xiaodan Liang
- Ali Farhadi
- Chunhua Shen
- Bo Li
- Chen Sun
Papers from Santosh Kumar Divvala's perspective
Ordered by how strongly the researchers Santosh Kumar Divvala trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- 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
- Going deeper with convolutions
Their papers
- You Only Look Once: Unified, Real-Time Object Detection (2015) — 46,861 citations
- Learning Everything about Anything: Webly-Supervised Visual Concept Learning (2014) — 325 citations
- An empirical study of context in object detection (2009) — 606 citations
- VisKE: Visual knowledge extraction and question answering by visual verification of relation phrases (2015) — 124 citations
- Asynchronous Temporal Fields for Action Recognition (2016) — 173 citations
- Video Relationship Reasoning Using Gated Spatio-Temporal Energy Graph (2019) — 112 citations
- DOCK: Detecting Objects by Transferring Common-Sense Knowledge (2018) — 31 citations