computer-vision-19
Visual Grounding
3260 papers • 126 benchmarks • 313 datasets
Visual Grounding (VG) aims to locate the most relevant object or region in an image, based on a natural language query. The query can be a phrase, a sentence, or even a multi-round dialogue. There are three main challenges in VG: What is the main focus in a query? How to understand an image? How to locate an object?
(Image credit: Open Source)
Benchmarks
These leaderboards are used to track progress in visual-grounding-19
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Actions
RefCOCO+ testA
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RefCOCO+ test B
RefCOCO+ test B
RefCOCO+ val
RefCOCO+ val
Libraries
iUse these libraries to find visual-grounding-19 models and implementations
4 papers 5,965
Datasets
No datasets available.