Momentum Sampler

How Is Computer Vision Evolving? A Comprehensive Review of Segmentation Large Models (SAM/SegGPT/SEEM)

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How Is Computer Vision Evolving? A Comprehensive Review of Segmentation Large Models (SAM/SegGPT/SEEM)

Source｜Heart of Autonomous Driving Image segmentation in computer vision is an important subfield that aims to assign each pixel in an image to different categories or objects. This technology is widely used in various applications such as image recognition, scene understanding, and medical image processing, demonstrating significant practical value. Previously, there were roughly two methods … Read more

Integrating SAM and Stable Diffusion: New AI Painting Techniques

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Integrating SAM and Stable Diffusion: New AI Painting Techniques

Since the launch of the SAM “Segment Anything” model, a wave of creative works has begun, with ideas and actions emerging! The developer from PaddlePaddle AI StudioThe Singing Alchemist has created an evolved version of SAM, integrating SAM and Stable Diffusion to achieve both “segmentation” and “generation” capabilities in one application, which is available for … Read more

Google Proposes New Framework Soft Diffusion: Correctly Scheduling, Learning, and Sampling from General Corruption Processes

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Google Proposes New Framework Soft Diffusion: Correctly Scheduling, Learning, and Sampling from General Corruption Processes

Follow our public account to discover the beauty of CV technology This article is adapted from Machine Heart, edited by Dan Jiang. Recently, diffusion models have become a research hotspot in the AI field. Researchers from Google Research and UT-Austin have fully considered the ‘corruption’ process in their latest study, proposing a design framework for … Read more