Shilei Wen
Computer Vision and Pattern Recognition · 2017–2020
A researcher in the Science corpus: 14 papers; trusts 1,243 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 414 citations into it; #10,674 of 21,575 by trust here, #3,613 by citations
- Artificial Intelligence — 195 citations into it; #31,506 of 35,345 by trust here, #10,798 by citations
- Model Architectures — 64 citations into it
- Generative Models — 44 citations into it
- Representation & Self-Supervised Learning — 42 citations into it
- Evaluation & Benchmarks — 38 citations into it
- Optimization & Training — 24 citations into it
- Media Technology — 19 citations into it
Whom Shilei Wen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Karen Simonyan
- Alex Krizhevsky
- Ross B. Girshick
- Andrew Zisserman
- Diederik P. Kingma
- Yoshua Bengio
- Yann LeCun
- Christian Szegedy
Who trusts Shilei Wen overall
- Christoph Feichtenhofer
- Limin Wang
- Bernard Ghanem
- Zuxuan Wu
- Chen Zhao
- Ali K. Thabet
- Gao Huang
- Hengduo Li
- Kristen Grauman
Papers from Shilei Wen's perspective
Ordered by how strongly the researchers Shilei Wen 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
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- BMN: Boundary-Matching Network for Temporal Action Proposal Generation (2019) — 726 citations
- Revisiting the Effectiveness of Off-the-shelf Temporal Modeling Approaches for Large-scale Video Classification (2017) — 49 citations
- Multi-Agent Reinforcement Learning Based Frame Sampling for Effective Untrimmed Video Recognition (2019) — 135 citations
- Exploiting Spatial-Temporal Modelling and Multi-Modal Fusion for Human Action Recognition (2018) — 19 citations
- Deep Metric Learning with Angular Loss (2017) — 548 citations
- Dynamic Computational Time for Visual Attention (2017) — 117 citations
- Dynamic Inference: A New Approach Toward Efficient Video Action Recognition (2020) — 37 citations
- Image Inpainting With Learnable Bidirectional Attention Maps (2019) — 265 citations
- Segment as Points for Efficient Online Multi-Object Tracking and Segmentation (2020) — 83 citations
- StNet: Local and Global Spatial-Temporal Modeling for Action Recognition (2018) — 145 citations
- STGAN: A Unified Selective Transfer Network for Arbitrary Image Attribute Editing (2019) — 366 citations
- RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning (2020) — 143 citations
- PP-YOLO: An Effective and Efficient Implementation of Object Detector (2020) — 345 citations
- Dynamic Instance Normalization for Arbitrary Style Transfer (2019) — 219 citations