Jing Chen

Computer Vision and Pattern Recognition · with Huang · 2019

A researcher in the Science corpus: 1 paper; trusts 26 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jing Chen trusts

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

  1. Rob Fergus (in Computer Vision and Pattern Recognition)
  2. Abhinav Kumar Gupta (in Computer Vision and Pattern Recognition)
  3. Trevor Darrell (in Computer Vision and Pattern Recognition)
  4. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  5. Jitendra Malik (in Computer Vision and Pattern Recognition)
  6. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  7. Kaiming He (in Computer Vision and Pattern Recognition)
  8. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  9. Thomas A. Funkhouser (in Computer Vision and Pattern Recognition)
  10. Martial Hebert (in Computer Vision and Pattern Recognition)

Papers from Jing Chen's perspective

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

  1. Fully convolutional networks for semantic segmentation
  2. Indoor Segmentation and Support Inference from RGBD Images
  3. ImageNet classification with deep convolutional neural networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Gradient-based learning applied to document recognition
  6. ImageNet: A large-scale hierarchical image database
  7. Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. Learning Rich Features from RGB-D Images for Object Detection and Segmentation
  10. Long Short-Term Memory

Their papers