Video Corpus Moment Retrieval

Video corpus moment retrieval (VCMR) aims to locate a specific moment within a large collection of untrimmed videos that best matches a given text query, bridging the gap between text and video understanding. Current research focuses on improving retrieval accuracy by addressing challenges like partial relevance of video segments to queries, leveraging multimodal information (visual and textual), and mitigating biases in training data. This involves developing sophisticated models that incorporate event reasoning, contrastive learning, and multi-modal fusion techniques, often within a two-stage retrieval and localization framework. VCMR advancements have significant implications for applications like video search engines, automated video summarization, and interactive video exploration.