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Video Description

The goal of automatic Video Description is to tell a story about events happening in a video. While early Video Description methods produced captions for short clips that were manually segmented to contain a single event of interest, more recently dense video captioning has been proposed to both segment distinct events in time and describe them in a series of coherent sentences. This problem is a generalization of dense image region captioning and has many practical applications, such as generating textual summaries for the visually impaired, or detecting and describing important events in surveillance footage.

Source: Joint Event Detection and Description in Continuous Video Streams

Papers

Showing 2130 of 104 papers

TitleStatusHype
Hawk: Learning to Understand Open-World Video AnomaliesCode3
TrafficVLM: A Controllable Visual Language Model for Traffic Video CaptioningCode2
X-VARS: Introducing Explainability in Football Refereeing with Multi-Modal Large Language Model0
JMI at SemEval 2024 Task 3: Two-step approach for multimodal ECAC using in-context learning with GPT and instruction-tuned Llama modelsCode0
Panda-70M: Captioning 70M Videos with Multiple Cross-Modality TeachersCode4
Multi-modal News Understanding with Professionally Labelled Videos (ReutersViLNews)0
ActionHub: A Large-scale Action Video Description Dataset for Zero-shot Action Recognition0
Attention Based Encoder Decoder Model for Video Captioning in Nepali (2023)0
Multi Sentence Description of Complex Manipulation Action Videos0
CLearViD: Curriculum Learning for Video Description0
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