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
8 papers · 1 filter
MR image reconstruction using deep density priors
Kerem C. Tezcan, Christian F. Baumgartner, Roger Luechinger +2
Algorithms for Magnetic Resonance (MR) image reconstruction from undersampled measurements exploit prior information to compensate for missing k-space data. Deep learning (DL) prov…
Appearance-and-Relation Networks for Video Classification
Limin Wang, Wei Li, Wen Li +1
Spatiotemporal feature learning in videos is a fundamental problem in computer vision. This paper presents a new architecture, termed as Appearance-and-Relation Network (ARTNet), t…
Temporal Segment Networks for Action Recognition in Videos
Limin Wang, Yuanjun Xiong, Zhe Wang +4
Deep convolutional networks have achieved great success for image recognition. However, for action recognition in videos, their advantage over traditional methods is not so evident…
Magnetic-Visual Sensor Fusion based Medical SLAM for Endoscopic Capsule Robot
Mehmet Turan, Yasin Almalioglu, Hunter Gilbert +3
A reliable, real-time simultaneous localization and mapping (SLAM) method is crucial for the navigation of actively controlled capsule endoscopy robots. These robots are an emergin…
Temporal Action Detection with Structured Segment Networks
Yue Zhao, Yuanjun Xiong, Limin Wang +3
Detecting actions in untrimmed videos is an important yet challenging task. In this paper, we present the structured segment network (SSN), a novel framework which models the tempo…
UntrimmedNets for Weakly Supervised Action Recognition and Detection
Limin Wang, Yuanjun Xiong, Dahua Lin +1
Current action recognition methods heavily rely on trimmed videos for model training. However, it is expensive and time-consuming to acquire a large-scale trimmed video dataset. Th…
Convolutional Oriented Boundaries: From Image Segmentation to High-Level Tasks
Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Pablo Arbeláez +1
We present Convolutional Oriented Boundaries (COB), which produces multiscale oriented contours and region hierarchies starting from generic image classification Convolutional Neur…
Reconstructing Subject-Specific Effect Maps
Ender Konukoglu, Ben Glocker
Predictive models allow subject-specific inference when analyzing disease related alterations in neuroimaging data. Given a subject's data, inference can be made at two levels: glo…