Zhaoyang Liu
Computer Vision and Pattern Recognition · arXiv.org · 2020–2025
A researcher in the Science corpus: 6 papers; trusts 745 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 340 citations into it
- Artificial Intelligence — 290 citations into it
- Model Architectures — 31 citations into it
- Biomedical Engineering — 24 citations into it
- Computational Mechanics — 13 citations into it
- Optimization & Training — 12 citations into it
- 3D Vision & Pose — 11 citations into it
- Control and Systems Engineering — 10 citations into it
Whom Zhaoyang Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Karen Simonyan
- Ross B. Girshick
- Andrew Zisserman
- Christian Szegedy
- Yoshua Bengio
- Yann LeCun
- Ilya Sutskever
Who trusts Zhaoyang Liu overall
Papers from Zhaoyang Liu's perspective
Ordered by how strongly the researchers Zhaoyang 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- TAM: Temporal Adaptive Module for Video Recognition (2020) — 374 citations
- Dynamic Sampling Networks for Efficient Action Recognition in Videos (2020) — 85 citations
- InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models (2025) — 1,590 citations
- InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency (2025) — 1,136 citations
- Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling (2024) — 1,631 citations
- MotionBERT: A Unified Perspective on Learning Human Motion Representations (2022) — 371 citations