Papers › Hierarchical Conditional Relation Networks for Video Question Answering
Hierarchical Conditional Relation Networks for Video Question Answering
Thao Minh Le, Vuong Le, Svetha Venkatesh, Truyen Tran
Video question answering (VideoQA) is challenging as it requires modeling capacity to distill dynamic visual artifacts and distant relations and to associate them with linguistic concepts. We introduce a general-purpose reusable neural unit called Conditional Relation Network (CRN) that serves as a building block to construct more sophisticated structures for representation and reasoning over video. CRN takes as input an array of tensorial objects and a conditioning feature, and computes an array of encoded output objects. Model building becomes a simple exercise of replication, rearrangement and stacking of these reusable units for diverse modalities and contextual information. This design thus supports high-order relational and multi-step reasoning. The resulting architecture for VideoQA is a CRN hierarchy whose branches represent sub-videos or clips, all sharing the same question as the contextual condition. Our evaluations on well-known datasets achieved new SoTA results, demonstrating the impact of building a general-purpose reasoning unit on complex domains such as VideoQA.
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Code
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Video Question Answering | SUTD-TrafficQA | HCRN | 1/2 | 63.79 | #4 of 6 | Archive leaderboard | report |
| Video Question Answering | SUTD-TrafficQA | HCRN | 1/4 | 36.49 | #4 of 6 | Archive leaderboard | report |
| Visual Question Answering (VQA) | MSRVTT-QA | HCRN | Accuracy | 0.356 | #28 of 34 | Archive leaderboard | report |
| Visual Question Answering (VQA) | MSVD-QA | HCRN | Accuracy | 0.361 | #32 of 36 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
Introduced by this paper: CRN
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