VideoQA D
AI benchmark · Multimodal
- Domains
- Multimodal
- Tier
- D why
- Snapshot
What is VideoQA?
DeepMind's 1H-VideoQA tests recall and reasoning over videos lasting 40 to 90 minutes. The current 101-question, five-choice task remains separate from the original 126-question set.
Lineage
Benchmarks this one is built on and built from: versions, subsets, extensions and the indexes that combine them.
Derived benchmarks
ActivityNet-QA subset
“we construct a new benchmark dataset \emph{ActivityNet-QA} for evaluating VideoQA performance.”
arxiv.org/e-print/1906.02467 ↗MSRVTT-QA extension
“For our experiments, we create two VideoQA datasets named MSVD-QA and MSRVTT-QA.”
github.com/xudejing/video-question-answering ↗
Tier D
Long tail: little or no usage data yet.
How much stands behind a tier: usage, who backs it, a confirmed line from its own site or paper, and a clear read on X. High with three of the four, medium with two, low otherwise.
- no usage data
- in curated RL directories (1 pt)
How we got to tier D
- Adoption: no usage data. Tier D.
- Not yet read on X.
- In curated RL directories: 1 point, a floor of none.
- Not yet confirmed by a line from its own site or paper.
A clear view on X moves a tier one step up or down; most entries don't move. How tiers work.
Not on the map yet: no line from its own site or paper places it in a domain.
Next: browse all benchmarks. Entry from the RL Research daily scrape of public sources, 2026-10-21 snapshot.