Object Tracking Benchmark (OTB) is a visual tracking benchmark that is widely used to evaluate the performance of a visual tracking algorithm. The dataset contains a total of 100 sequences and each is annotated frame-by-frame with bounding boxes and 11 challenge attributes. OTB-2013 dataset contains 51 sequences and the OTB-2015 dataset contains all 100 sequences of the OTB dataset.
398 PAPERS • 4 BENCHMARKS
TrackingNet is a large-scale tracking dataset consisting of videos in the wild. It has a total of 30,643 videos split into 30,132 training videos and 511 testing videos, with an average of 470,9 frames.
183 PAPERS • 2 BENCHMARKS
VOT2016 is a video dataset for visual object tracking. It contains 60 video clips and 21,646 corresponding ground truth maps with pixel-wise annotation of salient objects.
111 PAPERS • 1 BENCHMARK
VOT2017 is a Visual Object Tracking dataset for different tasks that contains 60 short sequences annotated with 6 different attributes.
54 PAPERS • 2 BENCHMARKS
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.
12 PAPERS • 1 BENCHMARK
VOT2020 is a Visual Object Tracking benchmark for short-term tracking in RGB.
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VOT2019 is a Visual Object Tracking benchmark for short-term tracking in RGB.
4 PAPERS • 1 BENCHMARK