Meta開源長視頻LLM項目LongVU：可過濾重複幀 高效精準理解長視頻內容
最近，Meta AI 團隊帶來了 LongVU，這是一種新穎的時空自適應壓縮機制，旨在提升長視頻的語言理解能力。傳統的多模態大型語言模型（MLLMs）在處理長視頻時面臨着上下文長度的限制，而 LongVU 正是爲了解決這一難題而誕生。LongVU 的工作原理主要通過過濾重複幀、跨幀token壓縮等方法來高效使用上下文長度，能夠在保持視頻視覺細節的同時減少視頻中的冗餘信息。具體來說，團隊使用 DINOv2的特徵來剔除那些高度相似的冗餘幀。接着，通過文本引導的跨模態查詢，實現了選擇性地減少幀特徵
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