Bing Wang

Computer Vision and Pattern Recognition · with Tang · 2022

A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Bing Wang trusts

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

  1. Kaiming He (in Computer Vision and Pattern Recognition)
  2. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  3. Shaoqing Ren (in Computer Vision and Pattern Recognition)
  4. X. Zhang (in Computer Vision and Pattern Recognition)
  5. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  6. Piotr Doll'ar (in Computer Vision and Pattern Recognition)
  7. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  8. Jitendra Malik (in Computer Vision and Pattern Recognition)
  9. Karen Simonyan (in Computer Vision and Pattern Recognition)
  10. Raquel Urtasun (in Computer Vision and Pattern Recognition)

Papers from Bing Wang's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. Feature Pyramid Networks for Object Detection
  3. Are we ready for autonomous driving? The KITTI vision benchmark suite
  4. ImageNet classification with deep convolutional neural networks
  5. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
  6. ImageNet: A large-scale hierarchical image database
  7. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space (Neural Information Processing Systems)
  8. VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection (2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition)
  9. Multi-view 3D Object Detection Network for Autonomous Driving
  10. Gradient-based learning applied to document recognition

Their papers