Madtempo: An Interactive System For Multi-event Temporal Video Retrieval With Query Augmentation

Abstract

The rapid expansion of video content across online platforms has accelerated the need for retrieval systems capable of understanding not only isolated visual moments but also the temporal structure of complex events. Existing approaches often fall short in modeling temporal dependencies across multiple events and in handling queries that reference unseen or rare visual concepts. To address these challenges, we introduce MADTempo, a video retrieval framework developed by our team, AIO_Trinh, that unifies temporal search with web-scale visual grounding. Our temporal search mechanism captures event-level continuity by aggregating similarity scores across sequential video segments, enabling coherent retrieval of multi-event queries. Complementarily, a Google Image Search-based fallback module expands query representations with external web imagery, effectively bridging gaps in pretrained visual embeddings and improving robustness against out-of-distribution (OOD) queries. Together, these c

Stats

• citations0
• S2 citations—
• github stars0
• HF likes0
• heat score0.00
• arxiv keyvu2025madtempo

Related papers

• Enhanced Multimodal Video Retrieval System: Integrating Query Expansion And Cross-modal Temporal Event Retrieval (2025)0.00
• Towards Efficient And Robust Moment Retrieval System: A Unified Framework For Multi-granularity Models And Temporal Reranking (2025)2.26
• A Lightweight Moment Retrieval System With Global Re-ranking And Robust Adaptive Bidirectional Temporal Search (2025)3.58
• Unified Interactive Multimodal Moment Retrieval Via Cascaded Embedding-reranking And Temporal-aware Score Fusion (2025)0.00
• Tempme: Video Temporal Token Merging For Efficient Text-video Retrieval (2024)2.86
• Multivent 2.0: A Massive Multilingual Benchmark For Event-centric Video Retrieval (2024)3.58
• Mamfusion: Multi-mamba With Temporal Fusion For Partially Relevant Video Retrieval (2025)1.69
• Graph Based Temporal Aggregation For Video Retrieval (2020)0.00