Predict, Then Retrieve: Cross-Instance Future-State Retrieval from Video Prefixes
We introduce Predictive State Retrieval (PSR), a task in which a model observes a short video prefix and a temporal question about an object's future state, then retrieves instances from other videos or images that depict that state. Unlike action anticipation, which predicts a label, moment retrieval, which localizes an observed event within a video, or video generation, which synthesizes pixels, PSR combines anticipation with cross-instance retrieval across multiple temporal horizons. We construct a benchmark from four datasets with graded, human-validated ground truth, difficulty tiers, and an oracle ceiling. We also propose LFTR, a lightweight retriever with frozen encoders that predi...
| Authors | Quynh Vo, Thong Nguyen, Vinh-Hien Do et al. |
|---|---|
| Primary category | cs.CV |
| Published | 5 August 2026 |
| Last updated at source | 5 August 2026 |
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