Javier Civera
Computer Vision and Pattern Recognition · 2006–2018
A researcher in the Science corpus: 5 papers; trusts 285 researchers and is trusted by 366 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 95 citations into it; #2,136 of 21,575 by trust here, #4,152 by citations
- Aerospace Engineering — 66 citations into it; #546 of 6,421 by trust here, #1,320 by citations
- Artificial Intelligence — 23 citations into it; #11,343 of 35,345 by trust here, #8,210 by citations
- Electrical and Electronic Engineering — 10 citations into it; #3,174 of 16,539 by trust here, #9,402 by citations
- Evaluation & Benchmarks — 5 citations into it
- Representation & Self-Supervised Learning — 5 citations into it; #1,379 of 3,145 by trust here, #1,081 by citations
Whom Javier Civera trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Andrew J. Davison
- David G. Lowe
- Andrew Zisserman
- José M. M. Montiel
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Ross B. Girshick
- Antonio Torralba
- David Nistér
Who trusts Javier Civera overall
- Mingyang Li
- Raul Mur-Artal
- Anastasios I. Mourikis
- Carlos Campos
- José M. M. Montiel
- Andrew J. Davison
- Juan D. Tardós
- Shaojie Shen
- Hauke Strasdat
- Rui Wang
Papers from Javier Civera's perspective
Ordered by how strongly the researchers Javier Civera 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
- Attention is All you Need (Neural Information Processing Systems)
- 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
- Learning object class detectors from weakly annotated video (2012) — 498 citations
- Unified Inverse Depth Parametrization for Monocular SLAM (2006) — 473 citations
- Inverse Depth Parametrization for Monocular SLAM (2008) — 854 citations
- DynaSLAM: Tracking, Mapping, and Inpainting in Dynamic Scenes (2018) — 1,214 citations
- 1-Point RANSAC for extended Kalman filtering: Application to real-time structure from motion and visual odometry (2010) — 351 citations