Junchi Yan
Computer Vision and Pattern Recognition · 2017–2023
A researcher in the Science corpus: 22 papers; trusts 1,992 researchers and is trusted by 34 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 786 citations into it; #4,359 of 21,575 by trust here, #3,875 by citations
- Artificial Intelligence — 385 citations into it
- Aerospace Engineering — 150 citations into it; #1,192 of 6,421 by trust here, #1,703 by citations
- Media Technology — 113 citations into it; #3,512 of 3,621 by trust here, #2,598 by citations
- Model Architectures — 112 citations into it
- Representation & Self-Supervised Learning — 70 citations into it
- Signal Processing — 51 citations into it
- Evaluation & Benchmarks — 47 citations into it
Whom Junchi Yan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ross B. Girshick
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Yann LeCun
- Shaoqing Ren
- Ilya Sutskever
- Karen Simonyan
Who trusts Junchi Yan overall
- Xue Yang
- Jiaming Han
- Yue Zhou
- Wentong Li
- Xinhao Cai
- Qi Ming
- Zhaohui Zheng
- Donghao Luo
- Wentao Wang
- Jian Ding
Papers from Junchi Yan's perspective
Ordered by how strongly the researchers Junchi Yan 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
- Unsupervised Deep Learning for Optical Flow Estimation (2017) — 325 citations
- Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline (2022) — 395 citations
- SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects (2018) — 887 citations
- R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object (2019) — 1,161 citations
- Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss (2021) — 609 citations
- Deep Extreme Multi-label Learning (2017) — 133 citations
- From Canonical Correlation Analysis to Self-supervised Graph Neural Networks (2021) — 301 citations
- NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification (2023) — 429 citations
- Transformers in Time Series: A Survey (2022) — 1,549 citations
- Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting (2023) — 1,316 citations
- MMRotate: A Rotated Object Detection Benchmark using PyTorch (2022) — 454 citations
- ST-P3: End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learning (2022) — 499 citations
- Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergence (2021) — 567 citations
- Generalizing Face Forgery Detection with High-frequency Features (2021) — 592 citations
- DARTS-: Robustly Stepping out of Performance Collapse Without Indicators (2020) — 194 citations
- Dense Label Encoding for Boundary Discontinuity Free Rotation Detection (2020) — 298 citations
- Image Matching from Handcrafted to Deep Features: A Survey (2020) — 932 citations
- SCRDet++: Detecting Small, Cluttered and Rotated Objects via Instance-Level Feature Denoising and Rotation Loss Smoothing (2020) — 354 citations
- Discriminative Partial Domain Adversarial Network (2020) — 30 citations
- Arbitrary-Oriented Object Detection with Circular Smooth Label (2020) — 590 citations