L
Luc Van Gool
Researcher at Katholieke Universiteit Leuven
Publications - 1458
Citations - 137230
Luc Van Gool is an academic researcher from Katholieke Universiteit Leuven. The author has contributed to research in topics: Computer science & Segmentation. The author has an hindex of 133, co-authored 1307 publications receiving 107743 citations. Previous affiliations of Luc Van Gool include Microsoft & ETH Zurich.
Papers
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Proceedings ArticleDOI
3D reconstruction of freely moving persons for re-identification with a depth sensor
TL;DR: A novel method for creating 3D models of persons freely moving in front of a consumer depth sensor and how they can be used for long-term person re-identification is described and shown.
Proceedings ArticleDOI
I know what you did last summer: object-level auto-annotation of holiday snaps
TL;DR: The efficiency of the retrieval process is optimized by creating more compact and precise indices for visual vocabularies using background information obtained in the crawling stage of the system.
Posted Content
ComboGAN: Unrestrained Scalability for Image Domain Translation
TL;DR: This paper proposes a multi-component image translation model and training scheme which scales linearly - both in resource consumption and time required - with the number of domains and demonstrates its capabilities on a dataset of paintings by 14 different artists.
Book ChapterDOI
HPAT indexing for fast object/scene recognition based on local appearance
TL;DR: The paper describes a fast system for appearance based image recognition that uses local invariant descriptors and efficient nearest neighbor search to overcomes the drawbacks of most binary tree-like indexing techniques, namely the high complexity in high dimensional data sets and the boundary problem.
Book ChapterDOI
Know Your Surroundings: Exploiting Scene Information for Object Tracking
TL;DR: In this paper, the presence and locations of other objects in the surrounding scene can be propagated through the sequence and used to explicitly avoid distractor objects and eliminate target candidate regions.