Overview

Video captioning studies how to describe what happens in a clip, from a single concise sentence to dense, timestamped event descriptions and long-form narratives. Systems combine video-language models with temporal segmentation and grounding, frame selection, tracking or motion cues, and—in audiovisual settings—alignment between sounds, speakers, and visible events. Common test settings include short clips and instructional videos, using benchmarks such as MSR-VTT, VATEX, ActivityNet Captions, and YouCook2; newer evaluations also test factuality, temporal accuracy, entity consistency, and whether captions support downstream question answering. A central challenge is balancing completeness and fluent detail against hallucination, especially as videos grow longer, while standard text-overlap metrics often miss these qualities.

Latest papers

CardsList

68 papers10 papers in the last four weeks, up 25% on the four weeks before. 0.1% of all new papers.

  1. Stay in your Lane: Role Specific Queries with Overlap Suppression Loss for Dense Video Captioning

    Mar 12, 2026Seung Hyup Baek, Jimin Lee, Hyeongkeun Lee +1Dense Video CaptioningVideo Captioning

  2. TimeChat-Captioner: Scripting Multi-Scene Videos with Time-Aware and Structural Audio-Visual Captions

    Feb 9, 2026Linli Yao, Yuancheng Wei, Yaojie Zhang +12Audio-Visual UnderstandingVideo Captioning

  3. TEMPURA: Temporal Event Masked Prediction and Understanding for Reasoning in Action

    May 2, 2025Jen-Hao Cheng, Yi-Hao Peng, Huapeng Zhou +11Temporal Action SegmentationTemporal Video Grounding

  4. Natural Language Generation from Visual Events: State-of-the-Art and Key Open Questions

    Feb 18, 2025Aditya K Surikuchi, Raquel Fernández, Sandro PezzelleVisual StorytellingMultimodal Learning