Visual Question Answering Datasets

Dataset · Visual question answering

ViFailback-Dataset

SII-RHOS

ViFailback Dataset: Real-World Robotic Manipulation Failure Dataset with Visual Symbol Guidance A real-world dataset for diagnosing, correcting, and learning from robotic manipulation failures via visual symbols. ViFailback is a large-scale, real-world robotic manipulation failure dataset introduced in the CVPR 2026 paper "Diagnose, Correct, and Learn from Manipulation Failures via Visual Symbols". It introduces visual

WorldBench is a new benchmark designed to evaluate the physical understanding and prediction of modern world models and vision-language models. There are two components: The video based benchmark can be found in /scenes. There are 4 high-level categories for different physics concepts being tested. Within each, there are 3-5 scenes each with 25-50 variations. The text based benchmark is in /textualquestions. There are 4 JSON files, one per category. Code to run the evaluation for this benchmark along with instructions can be found here: https://drive.google.com/file/d/1TNHfV-mKiidl1eFWJyctBOodWJnCajA/view?usp=sharing

This repository is a provenance-preserving collection of spatial measurement questions for answer-supervised training. It is built from VSI-590K, SpaceVista-Full, HiSpatial-Data, and CA-VQA. SenseNova-SI-8M is intentionally out of scope for this release. The first deliverable is the complete master collection. Smaller and larger training views will be derived only after all eligible metric examples have been retained and audited; they are not early sampling quotas. - annotations/ /measurement.parquet: canonical question/answer rows. - manifests/ /mediainventory.jsonl: unique required media and usage. - audits/ /: selection counts, validation, checksums, and source policy. - media/ /.tar…