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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Journal ArticleDOI
Sub-Markov Random Walk for Image Segmentation
TL;DR: The experimental results demonstrate that the proposed subRW method outperforms previous RW algorithms for seeded image segmentation, and designs a new subRW algorithm with label prior to solve the segmentation problem of objects with thin and elongated parts.
Proceedings ArticleDOI
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth
TL;DR: In this article, the spatial embeddings of pixels belonging to the same instance are jointly learned to maximize the intersection-over-union of the resulting instance mask, which achieves state-of-the-art performance on the Cityscapes benchmark.
Omnidirectional vision based topological navigation
TL;DR: A novel system for autonomous mobile robot navigation with only an omnidirectional camera as sensor is presented, able to build automatically and robustly accurate topologically organised environment maps of a complex, natural environment.
Book ChapterDOI
Spatio-temporal Channel Correlation Networks for Action Classification
Ali Diba,Mohsen Fayyaz,Vivek Sharma,Mohammad Mahdi Arzani,Rahman Yousefzadeh,Juergen Gall,Luc Van Gool +6 more
TL;DR: By fine-tuning this network, this work beats the performance of generic and recent methods in 3D CNNs, which were trained on large video datasets, and fine- Tuned on the target datasets, e.g. HMDB51/UCF101 and Kinetics.
Proceedings ArticleDOI
Real-time 3D hand gesture interaction with a robot for understanding directions from humans
Michael Van den Bergh,Daniel Carton,Roderick de Nijs,Nikos Mitsou,Christian Landsiedel,Kolja Kuehnlenz,Dirk Wollherr,Luc Van Gool,Martin Buss +8 more
TL;DR: A Haarlet-based hand gesture recognition system is implemented to detect hand gestures in any orientation, and more in particular pointing gestures while extracting the 3D pointing direction.