Search Results for author:
Found 2 papers, 0 papers with code
FiGCLIP: Fine-Grained CLIP Adaptation via Densely Annotated Videos
We use the SRL and verb information to create rule-based detailed captions, making sure they capture most of the visual concepts.
Unsupervised Audio-Visual Lecture Segmentation
We formulate lecture segmentation as an unsupervised task that leverages visual, textual, and OCR cues from the lecture, while clip representations are fine-tuned on a pretext self-supervised task of matching the narration with the temporally aligned visual content.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
