AI News

Multimodal large Language Models (MLLMs), such as GeoQA, MathVista, SPHINX, and GPT-4V, have made great strides in interpreting mathematical problems and diagrams, yet there remains a need for a more integrated approach that combines textual analysis with accurate visual interpretation. A research team from the CUHK MMLab and the Shanghai Artificial Intelligence Laboratory has developed…

The advancements in multimodal large language models (MLLMs) such as ChatGPT have proved revolutionary in several fields. However, these models primarily use Transformer networks, which have quadratic computation complexity, reducing efficiency. Language-Only Models (LLMs), on the other hand, are restricted in their adaptability as they solely rely on language interactions. Attempting to improve this, researchers from…

In the field of computer vision and artificial intelligence, the typical approach has been to create larger models to improve visual understanding. However, researchers from UC Berkeley and Microsoft Research have proposed a new technique that challenges this trend. Their innovative method, known as Scaling on Scales (S2), aims to enhance visual understanding without necessarily…

NeuFlow, a state-of-the-art optical flow architecture developed by a research team from Northeastern University, is set to change the game in computer vision. Traditional methods have often struggled to balance computational efficiency with accuracy, especially when running on edge devices. However, NeuFlow introduces a unique approach that combines global-to-local processing and lightweight CNNs (Convolutional Neural…

In the current digital age, reconstructing 3D objects from 2D images is crucial for numerous applications, such as creating 3D models for e-commerce websites and aiding autonomous vehicle navigation. However, computers struggle to imitate the human ability to infer an object's shape from a 2D image without having prior knowledge of the camera poses. This…

Image Restoration (IR), a key feature in computer vision, recovers high-quality images from degraded versions. It seeks to improve dilapidated images like faded photographs or camera-shake-blurred images. Conventional methods have evolved to some degree, but diffusion models marked an advancement in this field, offering a robust IR solution. However, there was a bottleneck; these models…

Large Vision Language Models (LVLMs) have shown excellent performance in tasks that require comprehension of both text and images, with progress in image-text understanding and reasoning becoming particularly noticeable in region-level tasks like Referring Expression Comprehension (REC). Notably, models like Griffon have demonstrated excellent performance in tasks such as object detection, indicating significant advances in…