Contextual AI Introduces LENS: An AI Framework for Vision-Augmented Language Models that Outperforms Flamingo by 9% (56->65%) on VQAv2

Large Language Models (LLMs) have transformed natural language understanding in recent years, demonstrating remarkable aptitudes in semantic comprehension, query resolution, and text production, particularly in zero-shot and few-shot environments. As seen in Fig. 1(a), several methods have been put forth for using LLMs on tasks involving vision. An optical encoder may be trained to represent…

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Unity Announce the Release of Muse: A Text-to-Video Games Platform that lets you Create Textures, Sprites, and Animations with Natural Language

AI has been making waves in various industries, revolutionizing how we approach art and many other fields. Artificial intelligence has opened up new possibilities for creative expression and efficiency with its ability to analyze data, learn patterns, and generate content. One area where AI has mainly made its mark is in the realm of game…

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Meet FastSAM: The Breakthrough Real-Time Solution Achieving High-Performance Segmentation with Minimal Computational Load

The Segment Anything Model (SAM) is a newer proposal in the field. It’s a vision foundation concept that’s been hailed as a breakthrough. It may employ multiple possible user involvement prompts to segment any object in the image accurately. Using a Transformer model that has been extensively trained on the SA-1B dataset, SAM can easily…

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Researchers teach an AI to write better chart captions | MIT News

Chart captions that explain complex trends and patterns are important for improving a reader’s ability to comprehend and retain the data being presented. And for people with visual disabilities, the information in a caption often provides their only means of understanding the chart. But writing effective, detailed captions is a labor-intensive process. While autocaptioning techniques…

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Meet SDFStudio: An Unified and Modular Framework for Neural Implicit Surface Reconstruction Built on Top of the Nerfstudio Project

Over the past few years, there has been a rapid increase in several computer vision and computer graphics-related fields, especially surface reconstruction. The primary goal of this ever-changing field in 3D scanning is to efficiently recreate surfaces from given point clouds while meeting specific quality criteria. These algorithms aim to estimate the underlying geometry of…

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Web-Scale Training Unleashed: Deepmind Introduces OWLv2 and OWL-ST, the Game-Changing Tools for Open-Vocabulary Object Detection, Powered by Unprecedented Self-Training Techniques

Open-vocabulary object detection is a critical aspect of various real-world computer vision tasks. However, the limited availability of detection training data and the fragility of pre-trained models often lead to subpar performance and scalability issues. To tackle this challenge, the DeepMind research team introduces the OWLv2 model in their latest paper, “Scaling Open-Vocabulary Object Detection.”…

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Meet DORSal: A 3D Structured Diffusion Model for the Generation and Object-Level Editing of 3D Scenes

Artificial Intelligence is evolving with the introduction of Generative AI and Large Language Models (LLMs). Well-known models like GPT, BERT, PaLM, etc., are some great additions to the long list of LLMs that are transforming how humans and computers interact. In image generation, diffusion models have gained significant attention from researchers as these models capture…

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