Shilong Liu
Computer Vision and Pattern Recognition · arXiv.org · 2018–2024
A researcher in the Science corpus: 8 papers; trusts 630 researchers and is trusted by 17 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 228 citations into it; #7,072 of 21,575 by trust here, #3,302 by citations
- Artificial Intelligence — 148 citations into it; #19,895 of 35,345 by trust here, #5,970 by citations
- Model Architectures — 58 citations into it; #1,411 of 2,278 by trust here, #794 by citations
- Aerospace Engineering — 15 citations into it
- Optimization & Training — 10 citations into it
- Computer Graphics and Computer-Aided Design — 9 citations into it
Whom Shilong Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Ross B. Girshick
- Tsung-Yi Lin
- Shaoqing Ren
- David G. Lowe
- Geoffrey E. Hinton
- Alex Krizhevsky
- X. Zhang
- Yoshua Bengio
- Diederik P. Kingma
Who trusts Shilong Liu overall
- Hao Zhang
- Feng Li
- Zhuofan Zong
- Mingqiao Ye
- Siyi Liu
- Lei Ke
- Yingfei Liu
- Qiang Chen
- Shaoshuai Shi
- Lin Song
Papers from Shilong Liu's perspective
Ordered by how strongly the researchers Shilong 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
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- 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
- Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection (2023) — 4,547 citations
- Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation (2022) — 638 citations
- DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection (2022) — 2,919 citations
- DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR (2022) — 1,335 citations
- DN-DETR: Accelerate DETR Training by Introducing Query DeNoising (2022) — 1,199 citations
- Recognize Anything: A Strong Image Tagging Model (2023) — 432 citations
- Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks (2024) — 1,209 citations
- A review of 3D reconstruction techniques in civil engineering and their applications (2018) — 312 citations