A vision encoder is a necessary component for allowing many leading LLMs to be able to work with images uploaded by users.

The official repository for “Hierarchical Encoder-decoder for Image Captioning (HierCap)”. HierCap is a model to guide text generation with hierarchical visual information at three levels: global ...

Apple has taken on this challenge with the release of AIMv2, a family of open-set vision encoders designed to improve upon existing models in multimodal understanding and object recognition tasks.

The visual encoder generates latent representations that capture diverse visual insights. ... Each decoder uses the same representation as input because the shared representation possesses the ...

The encoder translates visual stimuli into corresponding brain activity patterns through convolutional neural networks (CNNs) that mimic the human visual cortex's hierarchical processing stages. The ...

Video-LLaMA is built on top of BLIP-2 and MiniGPT-4.It is composed of two core components: (1) Vision-Language (VL) Branch and (2) Audio-Language (AL) Branch. VL Branch (Visual encoder: ViT-G/14 + ...

The model is structured around an Encoder-Decoder framework, comprising encoders for Text, Emotion, Vision, and Context, alongside a Cross-Modal encoder and a Multimodal decoder. To adeptly navigate ...

Decoder-based LLMs can be broadly classified into three main types: encoder-decoder, causal decoder, and prefix decoder. Each architecture type exhibits distinct attention patterns. Encoder-Decoder ...

The visual encoder is tasked with converting image information into a format that the AI system can process. The more advanced this encoder is, the better MM1 can understand and interpret image ...

The research team commences with PaLI-3, an advanced VLM trained on WebLI, featuring image-text data exclusively. The visual encoder, a ViT-G/14 with 2 billion parameters, and the language model, ...