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- The Visual Object Tracking VOT2015 Challenge Results902
The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance and presents a new VOT 2015 dataset twice as large as in VOT2014 with full annotation of targets by rotated bounding boxes and per-frame attribute.
- The Sixth Visual Object Tracking VOT2018 Challenge Results804
The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative; results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years.
- The Visual Object Tracking VOT2016 Challenge Results776
The Visual Object Tracking challenge VOT2016 goes beyond its predecessors by introducing a new semi-automatic ground truth bounding box annotation methodology and extending the evaluation system with the no-reset experiment.
- The Visual Object Tracking VOT2014 Challenge Results588
The Visual Object Tracking challenge 2014, VOT2014, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance and introduces a new dataset with full annotation of targets by rotated bounding boxes and per-frame attribute.
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- FuCoLoT – A Fully-Correlational Long-Term Tracker77
The proposed FuCoLoT exploits the novel DCF constrained filter learning method to design a detector that is able to re-detect the target in the whole image efficiently and has an order of magnitude smaller memory footprint than its best-performing competitors and runs at 15 fps in a single CPU thread.
- The Thermal Infrared Visual Object Tracking VOT-TIR2016 Challenge Results66
A significant general improvement of results has been observed, which partly compensate for the more difficult sequences introduced into the dataset in VOT-TIR2016.
- The Enhanced Flock of Trackers57
The enhancements of the Flock of Trackers are new reliability predictors for the local trackers - the Neighbourhood consistency predictor and the Markov predictor, new rules for combining the predictions and introduction of a RANSAC-based estimator of object motion.
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- The VOT2013 challenge: overview and additional results21
An overview of the VOT2013 challenge is provided, its main results are pointed out, and the additional previously unpublished experiments and results are documented.
- FCLT - A Fully-Correlational Long-Term Tracker18
The proposed FuCoLoT exploits the novel DCF constrained filter learning method to design a detector that is able to re-detect the target in the whole image efficiently and has an order of magnitude smaller memory footprint than its best-performing competitors and runs at 15fps in a single CPU thread.
- Calibrated Out-of-Distribution Detection with a Generic Representation12
This work proposes a novel OOD method, called GROOD, that formulates the OOD detection as a Neyman-Pearson task with well calibrated scores and which achieves excellent performance, predicated by the use of a good generic representation.
- A Dataset for Semantic Segmentation in the Presence of Unknowns5
A novel anomaly segmentation dataset, ISSU, is proposed that features a diverse set of anomaly inputs from cluttered real-world environments, and provides a training, validation and test set for controlled in-domain evaluation.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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