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Video-Text Retrieval

Video-Text retrieval requires understanding of both video and language together. Therefore it's different to video retrieval task.

Papers

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Showing 76–100 of 111 papers

TitleStatusHype
Mask to reconstruct: Cooperative Semantics Completion for Video-text Retrieval—0
Memory Enhanced Embedding Learning for Cross-Modal Video-Text Retrieval—0
Multi-Scale Temporal Difference Transformer for Video-Text Retrieval—0
NAVERO: Unlocking Fine-Grained Semantics for Video-Language Compositionality—0
OmniVL:One Foundation Model for Image-Language and Video-Language Tasks—0
Rethinking Noisy Video-Text Retrieval via Relation-aware Alignment—0
RETTA: Retrieval-Enhanced Test-Time Adaptation for Zero-Shot Video Captioning—0
Retrieving and Highlighting Action with Spatiotemporal Reference—0
Stacked Convolutional Deep Encoding Network for Video-Text Retrieval—0
Synopses of Movie Narratives: a Video-Language Dataset for Story Understanding—0
Synopses of Movie Narratives: a Video-Language Dataset for Story Understanding—0
Tagging before Alignment: Integrating Multi-Modal Tags for Video-Text Retrieval—0
Text-Adaptive Multiple Visual Prototype Matching for Video-Text Retrieval—0
TokenFlow: Rethinking Fine-grained Cross-modal Alignment in Vision-Language Retrieval—0
Towards Understanding Camera Motions in Any Video—0
Uncertainty-Aware Alignment Network for Cross-Domain Video-Text Retrieval—0
Uncertainty-Aware Alignment Network for Cross-Domain Video-Text Retrieval—0
Uncertainty-aware sign language video retrieval with probability distribution modeling—0
Unified Loss of Pair Similarity Optimization for Vision-Language Retrieval—0
Unifying Latent and Lexicon Representations for Effective Video-Text Retrieval—0
V^2Dial: Unification of Video and Visual Dialog via Multimodal Experts—0
V^2Dial: Unification of Video and Visual Dialog via Multimodal Experts—0
Videoprompter: an ensemble of foundational models for zero-shot video understanding—0
ViLEM: Visual-Language Error Modeling for Image-Text Retrieval—0
ViSeRet: A simple yet effective approach to moment retrieval via fine-grained video segmentation—0
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