Younggun Cho

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Younggun Cho trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Zhengyou Zhang
  2. Michael Kaess
  3. Gaurav Pandey
  4. Aleksandr V. Segal
  5. Andreas Geiger

Papers from Younggun Cho's perspective

Ordered by how strongly the researchers Younggun Cho trusts endorse each paper. Same corpus, a different order for every researcher.

  1. The Cityscapes Dataset for Semantic Urban Scene Understanding
  2. Vision meets robotics: The KITTI dataset
  3. A Flexible New Technique for Camera Calibration
  4. ImageNet classification with deep convolutional neural networks
  5. Estimating uncertain spatial relationships in robotics
  6. iSAM: Incremental Smoothing and Mapping
  7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  8. The ApolloScape Dataset for Autonomous Driving
  9. Gradient-based learning applied to document recognition
  10. The EuRoC micro aerial vehicle datasets (Int. J. Robotics Res.)

Their papers