VOTChallenge (Visual Object Tracking)
The Visual Object Tracking (VOT) dataset is a collection of video sequences used for evaluating and benchmarking visual object tracking algorithms. It provides a standardized platform for researchers and practitioners to assess the performance of different tracking methods.
Benchmarks
| Trend | Task | Dataset Variant | Best Model | Paper | Code |
|---|---|---|---|---|---|
|
VOT2020
|
DAM4SAM
|
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VOT2017/18
|
SiamMask_E
|
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VOT2017
|
GFS-DCF
|
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VOT2016
|
SiamMask_E
|
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VOT2022
|
DAM4SAM
|
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VOT2019
|
TREG
|
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VOT2018
|
TREG
|
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VOT2014
|
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Papers
| Paper | Code | Results | Date | Stars |
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Dataset Loaders
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