Ferret: Refer and Ground at Any Granularity

Enabling spatial understanding in vision-language learning models remains a core research challenge. This understanding underpins two crucial capabilities: grounding and referring. Referring enables the model to accurately interpret the semantics of specific regions, while grounding involves using semantic descriptions to localize these regions. Developers have introduced Ferret, a Multimodal Large Language Model (MLLM), capable of […]

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