Wei Zhong
Computer Vision and Pattern Recognition · 2012–2023
A researcher in the Science corpus: 4 papers; trusts 249 researchers and is trusted by 29 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 93 citations into it; #5,220 of 21,575 by trust here, #9,305 by citations
- Media Technology — 40 citations into it
- Artificial Intelligence — 16 citations into it
- Computational Mechanics — 6 citations into it
- Electrical and Electronic Engineering — 6 citations into it
Whom Wei Zhong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Shai Avidan
- John Wright
- Junseok Kwon
- Jianchao Yang
- Boris Babenko
- Amit Adam
- Zdenek Kalal
- Ming-Hsuan Yang
- David A. Ross
- Baiyang Liu
Who trusts Wei Zhong overall
- Martin Danelljan
- Yi Wu
- Yang Li
- Chao Ma
- Fahad Shahbaz Khan
- Shengping Zhang
- Ming-Hsuan Yang
- Gustav Häger
- Lianghua Huang
- Jianming Zhang
Papers from Wei Zhong's perspective
Ordered by how strongly the researchers Wei Zhong 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)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Robust object tracking via sparsity-based collaborative model (2012) — 1,031 citations
- Robust Object Tracking via Sparse Collaborative Appearance Model (2014) — 333 citations
- Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation (2023) — 337 citations
- Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection (2022) — 1,145 citations