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3D Question Answering (3D-QA) datasets

archive 2025-07-28

5 datasets carry the task tag "3D Question Answering (3D-QA)" (the task itself: 3D Question Answering (3D-QA)), ordered by the archive's paper count. Page 1 of 1: 5 shown of 5. Facet routes are this site's own (the archive records the tag string, not a page).

The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.

Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets

3D Question Answering (3D-QA) datasets 1–5 of 5

ScanQA (ScanQA: 3D Question Answering for Spatial Scene Understanding)
We collected 41,363 questions and 58,191 answers, in- cluding 32,337 unique questions and 16,999 unique an- swers.
70 papers · 1 benchmark
SQA3D (Situated Question Answering in 3D Scenes)
SQA3D is a dataset for embodied scene understanding, where an agent needs to comprehend the scene it situates from an first person's perspective and answer questions.
58 papers · 3 benchmarks
We established a 3D evaluation benchmark, 3D MM-Vet, to assess the 4-level capacity in embodied interaction scenarios, varying from basic perception to control statements generation.
4 papers · 1 benchmark
Dataset of the Beacon3D benchmark: Unveiling the Mist over 3D Vision-Language Understanding: Object-centric Evaluation with Chain-of-Analysis.
2 papers · 0 benchmarks
Multi-modal situated reasoning in 3D scenes
2 papers · 0 benchmarks

Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.