Risheng Liu
Computer Vision and Pattern Recognition · 2011–2023
A researcher in the Science corpus: 10 papers; trusts 332 researchers and is trusted by 30 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 194 citations into it
- Media Technology — 77 citations into it; #1,720 of 3,621 by trust here, #1,079 by citations
- Artificial Intelligence — 25 citations into it
- Computational Mechanics — 17 citations into it; #1,911 of 10,001 by trust here, #3,559 by citations
- Atomic and Molecular Physics, and Optics — 12 citations into it
- Biomedical Engineering — 7 citations into it; #8,403 of 10,734 by trust here, #9,539 by citations
- Model Architectures — 7 citations into it
- Electrical and Electronic Engineering — 6 citations into it
Whom Risheng Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Karen Simonyan
- Diederik P. Kingma
- Yoshua Bengio
- Ross B. Girshick
- Yann LeCun
- Wenhan Yang
- Ilya Sutskever
Who trusts Risheng Liu overall
- Thierry Bouwmans
- Chongyi Li
- M. Islam
- Jinyuan Liu
- Hao Bian
- Shuhang Gu
- Lintao Peng
- Weidong Zhang
- Changqing Zhang
- Xiaogang Xu
Papers from Risheng Liu's perspective
Ordered by how strongly the researchers Risheng Liu 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- The Visual Object Tracking VOT2015 Challenge Results (2015) — 901 citations
- Retinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancement (2020) — 1,024 citations
- Learning a Deep Multi-Scale Feature Ensemble and an Edge-Attention Guidance for Image Fusion (2021) — 404 citations
- Unsupervised Misaligned Infrared and Visible Image Fusion via Cross-Modality Image Generation and Registration (2022) — 323 citations
- Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation (2023) — 337 citations
- Twin Adversarial Contrastive Learning for Underwater Image Enhancement and Beyond (2022) — 353 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
- Toward Fast, Flexible, and Robust Low-Light Image Enhancement (2022) — 313 citations
- Real-World Underwater Enhancement: Challenges, Benchmarks, and Solutions Under Natural Light (2019) — 748 citations
- Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation (2011) — 1,297 citations