Raviteja Vemulapalli
Computer Vision and Pattern Recognition · 2014–2023
A researcher in the Science corpus: 8 papers; trusts 870 researchers and is trusted by 157 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 218 citations into it; #2,682 of 21,575 by trust here, #3,124 by citations
- Artificial Intelligence — 129 citations into it; #23,485 of 35,345 by trust here, #18,586 by citations
- Model Architectures — 36 citations into it
- Media Technology — 28 citations into it; #1,561 of 3,621 by trust here, #1,923 by citations
- Human-Computer Interaction — 27 citations into it; #29 of 2,253 by trust here, #94 by citations
- Evaluation & Benchmarks — 24 citations into it
- Representation & Self-Supervised Learning — 20 citations into it
- Optimization & Training — 16 citations into it
Whom Raviteja Vemulapalli trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Ross B. Girshick
- Alex Krizhevsky
- Yann LeCun
- Karen Simonyan
- Diederik P. Kingma
- Yoshua Bengio
- Andrew Zisserman
- Ilya Sutskever
Who trusts Raviteja Vemulapalli overall
- Jun Liu
- Hossein Rahmani
- Pichao Wang
- Guillermo Garcia-Hernando
- Amir Shahroudy
- Mengyuan Liu
- Qiuhong Ke
- Mohammed Bennamoun
- Jacopo Cavazza
- Wanqing Li
Papers from Raviteja Vemulapalli's perspective
Ordered by how strongly the researchers Raviteja Vemulapalli 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- 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
- Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group (2014) — 1,475 citations
- Boosting Image-based Mutual Gaze Detection using Pseudo 3D Gaze (2020) — 21 citations
- Global Self-Attention Networks for Image Recognition (2020) — 33 citations
- Gaussian Conditional Random Field Network for Semantic Segmentation (2016) — 151 citations
- Frame-Recurrent Video Super-Resolution (2018) — 570 citations
- Rolling Rotations for Recognizing Human Actions from 3D Skeletal Data (2016) — 207 citations
- TiC-CLIP: Continual Training of CLIP Models (2023) — 52 citations
- Search to Distill: Pearls Are Everywhere but Not the Eyes (2019) — 73 citations