Weisi Lin
Computer Vision and Pattern Recognition · 2011–2023
A researcher in the Science corpus: 13 papers; trusts 564 researchers and is trusted by 23 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 299 citations into it; #5,485 of 21,575 by trust here, #5,620 by citations
- Media Technology — 144 citations into it; #592 of 3,621 by trust here, #556 by citations
- Evaluation & Benchmarks — 62 citations into it
- Cognitive Neuroscience — 32 citations into it
- Artificial Intelligence — 30 citations into it
- Model Architectures — 14 citations into it
- Atomic and Molecular Physics, and Optics — 11 citations into it
- Oncology — 6 citations into it
Whom Weisi Lin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Zhou Wang
- A. Bovik
- Hamid R. Sheikh
- Eero P. Simoncelli
- Damon M. Chandler
- Nikolay N. Ponomarenko
- Eric C. Larson
- Pina Marziliano
- Stefan Winkler
- Anish Mittal
Who trusts Weisi Lin overall
- Ke Gu
- Yanjiao Chen
- Guangtao Zhai
- Chaofeng Chen
- Damon M. Chandler
- Xiongkuo Min
- Kede Ma
- Yuming Fang
- Kaishun Wu
- Wencheng Wang
Papers from Weisi Lin's perspective
Ordered by how strongly the researchers Weisi Lin trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- A Patch-Structure Representation Method for Quality Assessment of Contrast Changed Images (2015) — 377 citations
- TOPIQ: A Top-Down Approach From Semantics to Distortions for Image Quality Assessment (2023) — 346 citations
- FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Sampling (2022) — 327 citations
- Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectives (2022) — 427 citations
- Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data (2018) — 402 citations
- Review of Visual Saliency Detection With Comprehensive Information (2018) — 384 citations
- No-Reference Quality Metric of Contrast-Distorted Images Based on Information Maximization (2017) — 313 citations
- The Analysis of Image Contrast: From Quality Assessment to Automatic Enhancement (2016) — 374 citations
- No-Reference Quality Assessment of Contrast-Distorted Images Based on Natural Scene Statistics (2015) — 359 citations
- No-Reference Image Sharpness Assessment in Autoregressive Parameter Space (2015) — 307 citations
- Image Quality Assessment Based on Gradient Similarity (2012) — 718 citations
- Saliency Detection in the Compressed Domain for Adaptive Image Retargeting (2012) — 332 citations
- Perceptual visual quality metrics: A survey (2011) — 968 citations