Datasets › VOT2014

VOT2014 (Visual Object Tracking Challenge 2014)

Introduced by Matej Kristan et al. in A Novel Performance Evaluation Methodology for Single-Target Trackers archive 2025-07-28

The dataset comprises 25 short sequences showing various objects in challenging backgrounds. Eight sequences are from the VOT2013 challenge (bolt, bicycle, david, diving, gymnastics, hand, sunshade, woman). The new sequences show complementary objects and backgrounds, for example a fish underwater or a surfer riding a big wave. The sequences were chosen from a large pool of sequences using a methodology based on clustering visual features of object and background so that those 25 sequences sample evenly well the existing pool.

Source: VOT2014

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Visual Object Tracking VOT2014 Expected Average Overlap (EAO) 1.047 Efficient Counterfactual Learning from Bandit Feedback — 1 Compare

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 12. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
Efficient Counterfactual Learning from Bandit Feedback 0 1 10 Sep 2018 not harvested

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

Unknown

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • VOT2014

1 variant name, as the archive lists them.

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