PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation Topics image-captioning visual-reasoning visual-question-answering ...

Image-guided Story Ending Generation (IgSEG) aims to continue natural language generation (NLG) following a peceived visual control. Vision-Controllable Language Model (VCLM) aligns a frozen vsiual ...

Learn how NVIDIA's Llama Nemotron Nano 8B delivers cutting-edge AI performance in document processing, OCR, and automation ...

In the real world, it can be challenging to annotate a large-scale dataset for all medical images, making few-shot medical image classification an important task. The latest advancements in ...

Microsoft releases a new version of its small language model family. Phi-3-vision understands images and answers simple questions about photos or graphs. It’s a small multimodal model.

At its core, the Llama 3.2 vision models (available in 11B and 90B parameters) leverage a pre-trained image encoder to process visual inputs, which are then passed through the language model.

Recent advances in the field of robotics have enabled the automation of various real-world tasks, ranging from the manufacturing or packaging of goods in many industry settings to the precise ...

Unlike most vision models at the time, Florence was both “unified” and “multimodal,” meaning it could (1) understand language as well as images and (2) handle a range of tasks rather than ...