Computer Vision

Unified Model for Controllable Multimodal Image Generation

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Unified Model for Controllable Multimodal Image Generation

Machine Heart Column Machine Heart Editorial Team Researchers from Salesforce AI, Northeastern University, and Stanford University proposed the MOE-style Adapter and Task-aware HyperNet to achieve multimodal conditional generation capabilities in UniControl. UniControl was trained on nine different C2I tasks, demonstrating strong visual generation capabilities and zero-shot generalization abilities. Paper link: https://arxiv.org/abs/2305.11147 Code link: https://github.com/salesforce/UniControl Project … Read more

How Multimodal Large Language Models (MLLMs) Are Reshaping Computer Vision

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How Multimodal Large Language Models (MLLMs) Are Reshaping Computer Vision

Interpretation: AI Generates the Future This article introduces the Multimodal Large Language Model (MLLM), its definition, applications using challenging prompts, and the top models that are reshaping computer vision. Table of Contents What is a Multimodal Large Language Model (MLLM)? Applications and Cases of MLLMs in Computer Vision Leading Multimodal Large Language Models Future Outlook … Read more

Overview of Convolutional Neural Networks in Artificial Intelligence

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Overview of Convolutional Neural Networks in Artificial Intelligence

Introduction Convolutional Neural Networks (CNN) are one of the most important and widely used models in the field of deep learning. Since their introduction in the 1980s, CNNs have achieved significant success in areas such as image processing, computer vision, and natural language processing. This article aims to review the basic principles, development history, main … Read more

Understanding Convolutional Neural Networks (CNN)

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Understanding Convolutional Neural Networks (CNN)

Hello everyone, today we are going to talk about an important concept in deep learning – Convolutional Neural Networks (CNN). Whether you are a programmer, a data scientist, or a friend interested in artificial intelligence, I believe that after reading this article, you will have a clear understanding of CNN. 1. What is Convolutional Neural … Read more

Overview of Deep Learning Convolutional Neural Networks (CNN): From Basic Technology to Research Prospects

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Overview of Deep Learning Convolutional Neural Networks (CNN): From Basic Technology to Research Prospects

Today 170+/10000, includes: Essentials – Technical Text Insights – Algorithm Thoughts Hot Topics – What Everyone is Watching Source丨Machine Heart Editor丨Algorithm Insights Convolutional Neural Networks (CNN) have achieved unprecedented success in the field of computer vision, but we still do not have a comprehensive understanding of the reasons behind their remarkable effectiveness. Recently, Isma Hadji … Read more

Overview: A Comprehensive Survey on Segment Anything Model (SAM)

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Overview: A Comprehensive Survey on Segment Anything Model (SAM)

Source丨Machine Heart Editor丨Extreme City Platform Extreme City Introduction This article is the first comprehensive study introducing the progress of the SAM foundational model. It focuses on the application of SAM in various tasks and data types, discussing its historical development, recent advancements, and profound impacts on widespread applications. Artificial Intelligence (AI) is evolving towards AGI, … Read more

Comprehensive Survey on Segment Anything Model (SAM)

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Comprehensive Survey on Segment Anything Model (SAM)

Source | Machine Heart Editor | Jishi Platform Jishi Introduction This paper is the first comprehensive research introducing the progress of the SAM base model, focusing on its applications in various tasks and data types, discussing its historical development, recent advancements, and the profound impact on widespread applications. Artificial Intelligence (AI) is evolving towards AGI, … Read more

Goodbye Traditional Monocular Vision! Depth Anything V2 Achieves 10x More Accurate Depth Estimation!

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Goodbye Traditional Monocular Vision! Depth Anything V2 Achieves 10x More Accurate Depth Estimation!

🫱Click here to join the group chat of 18 sub-fields (🔥Highly recommended)🫲 Paper Title: Depth Anything V2 Authors: Lihe Yang, Bingyi Kang, Zilong Huang, Zhen Zhao, Xiaogang Xu, Jiashi Feng, Hengshuang Zhao Project Address: https://depth-anything-v2.github.io/ Compiled by: xlh Reviewed by: Los Abstract: In monocular depth estimation research, the widely used labeled real images have many … Read more

An Overview of Self-Supervised Learning and End-to-End Autonomous Driving

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An Overview of Self-Supervised Learning and End-to-End Autonomous Driving

Introduction Tesla’s FSD has popularized self-supervised learning, and large models like GPT also utilize the concept of self-supervised learning. As we know, the cost of supervised learning is prohibitively high, especially for complex tasks, such as FSD systems. Tesla has collected training data exceeding 400 million kilometers, and without the help of an “automated labeling … Read more

Comprehensive Knowledge Graph of Face Recognition

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Comprehensive Knowledge Graph of Face Recognition

Source: Smart Things This article is approximately 6000 words, and it is recommended to read for 10+ minutes. This article comprehensively analyzes the principles of face recognition technology, the situation of talent in the field, application areas, and development trends. Since the second half of the 20th century, computer vision technology has gradually developed and … Read more