Qi Qian
Computer Vision and Pattern Recognition · 2014–2024
A researcher in the Science corpus: 7 papers; trusts 659 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 239 citations into it
- Artificial Intelligence — 200 citations into it
- Multimodal Learning — 100 citations into it
- Representation & Self-Supervised Learning — 50 citations into it
- Evaluation & Benchmarks — 42 citations into it
- Optimization & Training — 23 citations into it
- Model Architectures — 17 citations into it
- Natural Language Processing — 16 citations into it
Whom Qi Qian trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Kaiming He
- Geoffrey E. Hinton
- Ross B. Girshick
- Ilya Sutskever
- Andrew Zisserman
- Yoshua Bengio
- Christian Szegedy
- Diederik P. Kingma
- Yann LeCun
Who trusts Qi Qian overall
- Arthur Douillard
- Eli Schwartz
- Jinlin Guo
- Oren Rippel
- Xingyu Lin
- Karsten Roth
- Matthieu Cord
- Jiankang Deng
- Leonid Karlinsky
- Feng Zhou
Papers from Qi Qian's perspective
Ordered by how strongly the researchers Qi Qian 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)
- 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
- Fine-grained visual categorization via multi-stage metric learning (2014) — 155 citations
- Learning to Rank Proposals for Object Detection (2019) — 53 citations
- SoftTriple Loss: Deep Metric Learning Without Triplet Sampling (2019) — 432 citations
- mPLUG-OwI2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration (2023) — 705 citations
- mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models (2024) — 307 citations
- HiTeA: Hierarchical Temporal-Aware Video-Language Pre-training (2022) — 107 citations
- Dash: Semi-Supervised Learning with Dynamic Thresholding (2021) — 300 citations