A 3D animated visualization of an LLM with a walkthrough.

2024/06: We release VisionLLM v2, which is a generalist multimodal large language model to support hundres of vision-language tasks, covering visual understanding, perception and generation. VisionLLM Series. Contribute to OpenGVLab/VisionLLM development by creating an account on GitHub.

Jun 12, 2024 · We present VisionLLM v2, an end-to-end generalist multimodal large model (MLLM) that unifies visual perception, understanding, and generation within a single framework. Unlike traditional MLLMs limited to text output, VisionLLM …

May 18, 2023 · In this work, we present an LLM-based framework for vision-centric tasks, termed VisionLLM. This framework provides a unified perspective for vision and language tasks by treating images as a foreign language and aligning vision-centric tasks with language tasks that can be flexibly defined and managed using language instructions.

Jan 7, 2025 · Large Language Models (LLMs) designed for visual understanding and reasoning have evolved significantly, enabling advancements in image captioning, scene comprehension, video analysis, and...

Jun 1, 2024 · The LaVIT project aims to leverage the exceptional capability of LLM to deal with visual content. The proposed pre-training strategy supports visual understanding and generation with one unified framework.

Feb 25, 2025 · A pretrained LLM and a pretrained vision encoder can be used, with an added mapping network layer that aligns or projects the visual representation of an image to the LLM’s input space. LLaVA (Large Language and Vision Assistant) is an example of a VLM developed from pretrained models.

CVR-LLM is to capitalize on VLMs' visual perception proficiency and LLMs' extensive reasoning capability. Recent advancements in Vision-Language (VL) research have sparked new benchmarks for complex visual reasoning, challenging models' advanced reasoning ability.

Feb 26, 2025 · For more information about VLMs and visual AI agents, register for the upcoming Vision for All: Unlocking Video Analytics with AI Agents webinar. For more information about LLM prompting, see An Introduction to Large Language Models: Prompt Engineering and P-Tuning.

Mar 7, 2025 · View a PDF of the paper titled DSV-LFS: Unifying LLM-Driven Semantic Cues with Visual Features for Robust Few-Shot Segmentation, by Amin Karimi and 1 other authors View PDF HTML (experimental) Abstract: Few-shot semantic segmentation (FSS) aims to enable models to segment novel/unseen object classes using only a limited number of labeled examples.