VeRVE uses a shared MLLM backbone with contrastive alignment and LoRA training to surpass other MLLM methods on zero-shot video retrieval while enabling competitive moment retrieval and state-of-the-art composed retrieval without further training.
E5-v: Universal embeddings with multi- modal large language models, 2024
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VeRVE: Versatile Retrieval for Videos via Unified Embeddings
VeRVE uses a shared MLLM backbone with contrastive alignment and LoRA training to surpass other MLLM methods on zero-shot video retrieval while enabling competitive moment retrieval and state-of-the-art composed retrieval without further training.