ST-VQA

The ST-VQA dataset is used to evaluate Text Visual Question Answering (TextVQA) approaches by providing images along with questions that require understanding both visual content and textual elements within the scene.

Papers using ST-VQA (6)

When Big Models Train Small Ones: Label-Free Model Parity Alignment for Efficient Visual Question Answering using Small VLMs2025MGA-VQA: Secure And Interpretable Graph-augmented Visual Question Answering With Memory-guided Protection Against Unauthorized Knowledge Use2025Toward 3D Spatial Reasoning for Human-like Text-based Visual Question Answering2022 · 8 citesTAG: Boosting Text-VQA via Text-aware Visual Question-answer Generation2022 · 7 citesSceneGATE: Scene-Graph based co-Attention networks for TExt visual question answering2022 · 1 citesLocate Then Generate: Bridging Vision and Language with Bounding Box for Scene-Text VQA2023 · 1 cites