Shiqi Wang
Computer Vision and Pattern Recognition · IEEE transactions on circuits and systems for video technology (Print) · 2013–2019
A researcher in the Science corpus: 6 papers; trusts 258 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 107 citations into it; #20,035 of 21,575 by trust here, #11,083 by citations
- Artificial Intelligence — 30 citations into it; #32,688 of 35,345 by trust here, #28,481 by citations
- Media Technology — 22 citations into it
- Signal Processing — 22 citations into it
- Natural Language Processing — 16 citations into it; #5,264 of 5,688 by trust here, #4,983 by citations
- Evaluation & Benchmarks — 15 citations into it
- Generative Models — 11 citations into it
- Multimodal Learning — 10 citations into it
Whom Shiqi Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Zhou Wang
- Hamid R. Sheikh
- A. Bovik
- Diederik P. Kingma
- Eero P. Simoncelli
- Geoffrey E. Hinton
- Yoshua Bengio
- Kaiming He
- Alex Krizhevsky
- Yann LeCun
Who trusts Shiqi Wang overall
- Ke Gu
- Chongyi Li
- Ruotian Luo
- Wencheng Wang
- Peixian Zhuang
- Yang Wang
- Y. Shi
- Matteo Stefanini
- Weisi Lin
- Ron Mokady
Papers from Shiqi Wang's perspective
Ordered by how strongly the researchers Shiqi Wang 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)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- CNN-Based Bi-Directional Motion Compensation for High Efficiency Video Coding (2018) — 26 citations
- A Patch-Structure Representation Method for Quality Assessment of Contrast Changed Images (2015) — 377 citations
- Perceptual Video Coding Based on SSIM-Inspired Divisive Normalization (2013) — 129 citations
- VERI-Wild: A Large Dataset and a New Method for Vehicle Re-Identification in the Wild (2019) — 304 citations
- Image and Video Compression With Neural Networks: A Review (2019) — 419 citations
- Self-Critical N-Step Training for Image Captioning (2019) — 63 citations