Real-world user-generated videos, especially on platforms like TikTok, often feature rich and intertwined audio-visual content. However, existing video captioning benchmarks and models remain predominantly visual-centric, overlooking the crucial role of audio in conveying scene dynamics, speaker intent, and narrative context. This lack of full-modality datasets and lightweight, capable models hampers progress in fine-grained, multimodal video… See the full description on the dataset page:
https://huggingface.co/datasets/openinterx/UGC-VideoCap.
