  We introduce an audiovisual method for long-range text-to-video retrieval.
Unlike previous approaches designed for short video retrieval (e.g., 5-15
seconds in duration), our approach aims to retrieve minute-long videos that
capture complex human actions. One challenge of standard video-only approaches
is the large computational cost associated with processing hundreds of densely
extracted frames from such long videos. To address this issue, we propose to
replace parts of the video with compact audio cues that succinctly summarize
dynamic audio events and are cheap to process. Our method, named ECLIPSE
(Efficient CLIP with Sound Encoding), adapts the popular CLIP model to an
audiovisual video setting, by adding a unified audiovisual transformer block
that captures complementary cues from the video and audio streams. In addition
to being 2.92x faster and 2.34x memory-efficient than long-range video-only
approaches, our method also achieves better text-to-video retrieval accuracy on
several diverse long-range video datasets such as ActivityNet, QVHighlights,
YouCook2, DiDeMo and Charades.
