A scalable training-free pipeline using video segmentation, filtering, and off-the-shelf multimodal models creates DenseStep2M, a dataset of 100K videos and 2M detailed instructional steps that improves dense captioning, step grounding, and cross-modal retrieval.
End-to-end dense video captioning as sequence generation
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TemporalVLM adds timestamp-aware clip encoding and BiLSTM global aggregation to video LLMs, introduces the IndustryASM factory dataset, and reports outperformance on dense captioning, temporal grounding, highlight detection, and action segmentation.
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DenseStep2M: A Scalable, Training-Free Pipeline for Dense Instructional Video Annotation
A scalable training-free pipeline using video segmentation, filtering, and off-the-shelf multimodal models creates DenseStep2M, a dataset of 100K videos and 2M detailed instructional steps that improves dense captioning, step grounding, and cross-modal retrieval.
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TemporalVLM: Video LLMs for Temporal Reasoning in Long Videos
TemporalVLM adds timestamp-aware clip encoding and BiLSTM global aggregation to video LLMs, introduces the IndustryASM factory dataset, and reports outperformance on dense captioning, temporal grounding, highlight detection, and action segmentation.