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README.md

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 # PinpointQA: A Dataset and Benchmark for Small Object-Centric Spatial Understanding in Indoor Videos
 
-🎯 **PinpointQA** is a dataset and benchmark for **small object-centric spatial understanding in indoor videos**.
-
-It evaluates whether a model can detect a queried small object, ground it through nearby references, describe its final location precisely in natural language, and express the same grounded information in structured machine-readable form.
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 > **Important:** This repository releases **benchmark annotations** and **grounded intermediate spatial representations** only. It does **not** redistribute the original scene assets or converted video files.
 
-## ✨ Highlights
-
-- **1,024 scenes**
-- **10,094 QA pairs**
-- **4 benchmark tasks:** TPV, NRI, FSD, SSP
-- **102 canonical target categories**
-- Built from **ScanNet++** and **ScanNet200**
-
 ## 🧭 Overview
 
 PinpointQA focuses on a practical question: given a known small object such as a phone, charger, remote, or bottle, can a model determine whether it appears, localize it through nearby references, describe its position precisely, and provide an output that is directly useful for downstream systems?