801 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- ETH ZurichCH39 papers
- Chinese University of Hong KongHK6 papers
- KU LeuvenBE6 papers
- Shenzhen Institutes of Advanced TechnologyCN5 papers
- Chinese Academy of SciencesCN4 papers
- Imperial College LondonGB3 papers
- Johns Hopkins UniversityUS3 papers
- Nanjing UniversityCN2 papers
- Technical University of MunichDE2 papers
- University of California, IrvineUS2 papers
- University of Chinese Academy of SciencesCN2 papers
- University of Electronic Science and Technology of ChinaCN2 papers
4 papers · 2 filters
Knowledge Guided Disambiguation for Large-Scale Scene Classification with Multi-Resolution CNNs
Limin Wang, Sheng Guo, Weilin Huang +2
Convolutional Neural Networks (CNNs) have made remarkable progress on scene recognition, partially due to these recent large-scale scene datasets, such as the Places and Places2. S…
Weakly Supervised PatchNets: Describing and Aggregating Local Patches for Scene Recognition
Zhe Wang, Limin Wang, Yali Wang +2
Traditional feature encoding scheme (e.g., Fisher vector) with local descriptors (e.g., SIFT) and recent convolutional neural networks (CNNs) are two classes of successful methods…
Fast Optical Flow using Dense Inverse Search
Till Kroeger, Radu Timofte, Dengxin Dai +1
Most recent works in optical flow extraction focus on the accuracy and neglect the time complexity. However, in real-life visual applications, such as tracking, activity detection…
Locally-Supervised Deep Hybrid Model for Scene Recognition
Sheng Guo, Weilin Huang, Limin Wang +1
Convolutional neural networks (CNN) have recently achieved remarkable successes in various image classification and understanding tasks. The deep features obtained at the top fully…