Jorge P. Batista
Computer Vision and Pattern Recognition · 2012–2015
A researcher in the Science corpus: 8 papers; trusts 777 researchers and is trusted by 2,814 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 212 citations into it; #718 of 21,575 by trust here, #1,556 by citations
- Aerospace Engineering — 47 citations into it; #624 of 6,421 by trust here, #988 by citations
- Artificial Intelligence — 32 citations into it; #5,749 of 35,345 by trust here, #6,720 by citations
- 3D Vision & Pose — 20 citations into it; #364 of 689 by trust here, #443 by citations
- Media Technology — 20 citations into it
- Computational Mechanics — 19 citations into it
- Evaluation & Benchmarks — 18 citations into it; #1,371 of 3,147 by trust here, #2,330 by citations
- Computer Graphics and Computer-Aided Design — 12 citations into it
Whom Jorge P. Batista trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David G. Lowe
- João Carreira
- Geoffrey E. Hinton
- Ross B. Girshick
- Jitendra Malik
- Alex Krizhevsky
- Kaiming He
- Yann LeCun
- Andrew Zisserman
- Yoshua Bengio
Who trusts Jorge P. Batista overall
- Martin Danelljan
- Ross B. Girshick
- Jitendra Malik
- João Carreira
- Ming-Hsuan Yang
- Bharath Hariharan
- Fahad Shahbaz Khan
- Luc Van Gool
- Shubham Tulsiani
- Sanja Fidler
Papers from Jorge P. Batista's perspective
Ordered by how strongly the researchers Jorge P. Batista 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
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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
- Semantic Segmentation with Second-Order Pooling (2012) — 533 citations
- High-Speed Tracking with Kernelized Correlation Filters (2014) — 5,428 citations
- The Visual Object Tracking VOT2014 Challenge Results (2014) — 512 citations
- Exploiting the Circulant Structure of Tracking-by-Detection with Kernels (2012) — 2,356 citations
- Reconstructing PASCAL VOC (2014) — 191 citations
- Pedestrian detection combining RGB and dense LIDAR data (2014) — 201 citations
- Lifting Object Detection Datasets into 3D (2015) — 18 citations
- Semantic Segmentation with (2012) — 269 citations