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This AI Paper Introduces the Open-Vocabulary SAM: A SAM-Inspired Model Designed for Simultaneous Interactive Segmentation and Recognition

Marktechpost

Combining CLIP and the Segment Anything Model (SAM) is a groundbreaking Vision Foundation Models (VFMs) approach. SAM performs superior segmentation tasks across diverse domains, while CLIP is renowned for its exceptional zero-shot recognition capabilities. SAM, for instance, cannot recognize the segments it identifies.

AI 111
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Researchers from Tsinghua University and Harvard University introduces LangSplat: A 3D Gaussian Splatting-based AI Method for 3D Language Fields

Marktechpost

This field of open-ended language queries in 3D has attracted researchers due to its various applications in robotic navigation and manipulation, 3D semantic understanding, and editing. Consequently, a team of researchers from Tsinghua University and Harvard University has developed a method called LangSplat.

Robotics 110
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Advancements in Knowledge Distillation and Multi-Teacher Learning: Introducing AM-RADIO Framework

Marktechpost

Recently, Foundation Models (FMs) have emerged as large, general models trained on vast datasets, exemplified by CLIP and DINOv2, showcasing remarkable zero-shot performances in computer vision tasks. SAM is noted for its instance segmentation capabilities, attributed to its strong dense feature representations.

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Achieving accurate image segmentation with limited data: strategies and techniques

deepsense.ai

It all began with the Segment Anything Model (SAM) from Meta AI, followed by rapid advancements in zero- and few-shot image segmentation. Recently, the most popular approaches have utilized natural language as a proxy for describing new classes, exemplified by the CLIP model. Illustration of the CLIP training process.

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Segment Anything Model (SAM) Deep Dive – Complete 2024 Guide

Viso.ai

The Segment Anything Model (SAM), a recent innovation by Meta’s FAIR (Fundamental AI Research) lab, represents a pivotal shift in computer vision. SAM performs segmentation, a computer vision task , to meticulously dissect visual data into meaningful segments, enabling precise analysis and innovations across industries.

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Grounded-SAM Explained: A New Image Segmentation Paradigm?

Viso.ai

Before diving into Grounded Segment Anything (Grounded-SAM), let’s take a brief refresher on the core technologies that underly it. Segment Anything Model (SAM) Segment Anything (SAM) is a foundation model capable of segmenting every discernible entity within an image. What is Grounded-SAM?

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Data generation with diffusion models – part 2

deepsense.ai

Recently Meta AI was in the spotlight with the introduction of a groundbreaking new model, the Segment Anything Model (SAM) [1], along with the SA-1B Dataset consisting of 11m images with 1.1bn mask annotations. Researchers used a pre-trained GAN to generate a few images, which were then labeled by a human annotator.