VLM2Vec-V2: Unified Multimodal Embedding for Images, Videos & Documents
VLM2Vec-V2: A unified framework for multimodal embedding learning across images, videos, and documents. Outperforms existing models on various benchmarks.
VLM2Vec-V2: A unified framework for multimodal embedding learning across images, videos, and documents. Outperforms existing models on various benchmarks.
Revolutionize video search! Use open-source LLMs on AWS for semantic video search via text or image queries. Learn about the architecture, code, and limitations.
CompleteMe AI excels at restoring and editing human images using reference images, outperforming existing methods in benchmarks. Learn about its features and limitations.
MirrorVerse improves AI reflection rendering in diffusion models. A new dataset & model, MirrorFusion 2.0, achieves superior results in tests, addressing limitations of previous approaches.
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