In recent years, multimodal large-scale language models have made significant progress in the field of artificial intelligence. Today, the editor of Downcodes will introduce a model called ORYX, which was jointly developed by researchers from Tsinghua University, Tencent and Nanyang Technological University. It has demonstrated impressive capabilities in the field of visual processing. ORYX is not just a simple image recognition system. It can understand the spatio-temporal relationship in images, videos and 3D scenes, and can even discern the story behind the content like humans. It can be called the "Transformer" in the field of visual processing. Let’s take a closer look at what makes ORYX unique.
Today, with the rapid development of artificial intelligence, a multi-modal large-scale language model called ORYX is quietly changing our understanding of AI's ability to understand the visual world. This AI system, jointly developed by researchers from Tsinghua University, Tencent and Nanyang Technological University, can be called a Transformer in the field of visual processing.
ORYX, the full name of Oryx Multi-Modal Large Language Models, is an AI model specially designed to process spatio-temporal understanding of images, videos and 3D scenes. Its core advantage is that it can not only understand visual content like humans, but also understand the connections between the content and the stories behind it.
One of the highlights of this AI system is its ability to process visual input at any resolution. Whether it's blurry old photos or high-definition videos, ORYX can handle it easily. This is thanks to its pre-trained model OryxViT, which can convert images of different resolutions into a unified format understandable by AI.
Even more amazing is ORYX's dynamic compression capabilities. Faced with long-term video input, it can intelligently compress information and retain key content without distortion. It's like distilling a heavy book into a rich note card, which not only retains the core information, but also greatly improves processing efficiency.
The working principle of ORYX mainly relies on two core components: the visual encoder OryxViT and the dynamic compression module. The former is responsible for processing diverse visual inputs, while the latter ensures that large-capacity data such as long-term videos can be processed efficiently.
In practical applications, ORYX has shown amazing potential. It can not only deeply understand video content, including objects, plots and actions, but also accurately grasp the position and relationship of objects in 3D space. This comprehensive visual understanding capability brings unlimited possibilities to future human-computer interaction, intelligent monitoring, autonomous driving and other fields.
It is worth mentioning that ORYX has performed well in multiple visual-language benchmarks, especially in spatial and temporal understanding of images, videos, and multi-view 3D data, showing leading advantages.
The innovation of ORYX lies not only in its powerful processing capabilities, but also in that it opens up a new paradigm for AI visual understanding. It can process visual input at native resolution while efficiently processing long videos through dynamic compression technology. This kind of flexibility and efficiency is difficult to achieve by other AI models.
As technology continues to advance, ORYX is expected to play a more important role in the future AI field. It will not only help machines better understand our visual world, but may also provide new ideas for the simulation of human cognitive processes.
Paper address: https://arxiv.org/pdf/2409.12961
ORYX's multi-modal capabilities and efficient processing methods have brought new possibilities to the field of AI vision, and its future development is worth looking forward to. The editor of Downcodes believes that as the technology continues to mature, ORYX will play an important role in more fields and promote the continuous progress of artificial intelligence technology.