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- Revealing DeDoDe v2: How to innovate key point detection technology to make AI's 'eyes” brighter?
- 1. Technological innovation, DeDoDev2 emerged as the times require. In the fields of image processing and computer vision, key point detection is the basis of many applications, such as target recognition, image matching, three-dimensional reconstruction, etc. However, traditional key point detection technology often has problems such as inaccurate detection and vulnerability to noise interference. In order to solve these problems, scientific research teams such as Linköping University launched DeDoDev2, a new key point detector, which makes targeted improvements and optimizations through in-depth analysis of DeDoDe's shortcomings. 2. Breaking through the bottleneck, DeDoDev2’s three major innovations solve the problem of key point clustering. In DeDoDe, researchers found that key points tend to cluster in specific areas, resulting in insufficient detection in other areas.
- AI 1148 2024-05-09 14:55:01
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- LidaRF: Studying LiDAR Data for Street View Neural Radiation Fields (CVPR\'24)
- Light-realistic simulation plays a key role in applications such as autonomous driving, where advances in neural network radiated fields (NeRFs) may enable better scalability by automatically creating digital 3D assets. However, the reconstruction quality of street scenes suffers due to the high collinearity of camera motion on the streets and sparse sampling at high speeds. On the other hand, the application often requires rendering from a camera perspective that deviates from the input perspective to accurately simulate behaviors such as lane changes. LidaRF presents several insights that allow better utilization of lidar data to improve the quality of NeRF in street views. First, the framework learns geometric scene representations from lidar data, which are combined with an implicit mesh-based decoder to provide stronger geometric information provided by the displayed point cloud.
- AI 828 2024-05-09 13:31:37
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- Nintendo blitzes GitHub, deleting more than 8,000 emulator code repositories overnight
- Nintendo Blitzes GitHub! 8535 code bases were removed overnight. As long as it contains the YuzuSwitch emulator code, it is said to have illegally bypassed Nintendo's technical protection measures and run illegal pirated Switch games. GitHub also responded. Developers have time to delete or change infringing content. In addition, GitHub provides legal resources and guidance for developers on how to submit DMCA (a U.S. copyright law) counter-notification. As soon as this incident came out, netizens also exploded, with voices supporting Nintendo and Yuzu. Some netizens suggested, don’t make any noise: let’s vote with our wallets! Some netizens thought they were deleting all Nintendo emulators: Fortunately, it was just with Yu
- AI 895 2024-05-09 12:46:28
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- HKU's large open source graph basic model OpenGraph: strong generalization ability, forward propagation to predict new data
- There is a new way to alleviate the data starvation problem in the field of graph learning! OpenGraph, a basic graph-based model specifically designed for zero-shot prediction on a variety of graph datasets. The Chao Huang team, head of the Data Intelligence Laboratory at the University of Hong Kong, also proposed improvement and adjustment techniques for the model to improve the model's adaptability to new tasks. Currently, this work has been posted on GitHub. Introducing data augmentation techniques, this work is an in-depth exploration of strategies to enhance the generalization ability of graphical models (especially when there are significant differences in training and test data). OpenGraph is a general graph structure model that performs forward propagation through propagation prediction to achieve zero-sample prediction of new data. To achieve their goals, the team
- AI 337 2024-05-09 12:01:02
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- Application of algorithms in the construction of 58 portrait platform
- 1. Background of the Construction of 58 Portraits Platform First of all, I would like to share with you the background of the construction of the 58 Portrait Platform. 1. The traditional thinking of the traditional profiling platform is no longer enough. Building a user profiling platform relies on data warehouse modeling capabilities to integrate data from multiple business lines to build accurate user portraits; it also requires data mining to understand user behavior, interests and needs, and provide algorithms. side capabilities; finally, it also needs to have data platform capabilities to efficiently store, query and share user profile data and provide profile services. The main difference between a self-built business profiling platform and a middle-office profiling platform is that the self-built profiling platform serves a single business line and can be customized on demand; the mid-office platform serves multiple business lines, has complex modeling, and provides more general capabilities. 2.58 User portraits of the background of Zhongtai portrait construction
- AI 553 2024-05-09 09:01:10
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- Explore automated work management tools and their benefits in 2024
- In the fast-paced business world, efficiency and productivity are paramount. To stay ahead of the curve, organizations are increasingly turning to automated work management tools. But what exactly are these tools, and how can they benefit businesses in 2024? Automated work management tools comprise a range of software solutions designed to streamline and optimize every aspect of an organization’s workflow. These tools automate repetitive tasks, facilitate collaboration, and provide insights to enhance the decision-making process. In today's highly competitive environment, businesses are challenged to do more with fewer resources. Automated work management tools provide a way to achieve this by eliminating manual inefficiencies and maximizing capital utilization. They enable teams to focus on high value while automating routine activities
- AI 635 2024-05-08 20:40:05
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- 7262 papers were submitted, ICLR 2024 became a hit, and two domestic papers were nominated for outstanding papers.
- This year, a total of 5 outstanding paper awards and 11 honorable mentions were selected. ICLR stands for International Conference on Learning Representations (International Conference on Learning Representations). This year is the twelfth conference, held in Vienna, Austria, from May 7th to 11th. In the machine learning community, ICLR is a relatively "young" top academic conference. It is hosted by deep learning giants and Turing Award winners Yoshua Bengio and Yann LeCun. It just held its first session in 2013. However, ICLR quickly gained wide recognition from academic researchers and is considered the top academic conference on deep learning. This session received a total of 726
- AI 1115 2024-05-08 20:34:24
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- Large models are popular with digital people: one sentence can be customized in 5 minutes, and you can hold it while dancing, hosting and delivering goods
- In as little as 5 minutes, you can create a 3D digital human that can go directly to work. This is the latest shock that large models have brought to the field of digital humans. Just like this, one sentence describes the demand: the generated digital people can directly enter the live broadcast room and serve as anchors. It's no problem to dance in a girl group dance. During the entire production process, just say whatever comes to mind. The large model can automatically disassemble the requirements, and you can get designs and modify ideas instantly. △With 2x speed, you no longer have to worry about the boss/Party A’s ideas being too novel. Such Vincent digital human technology comes from the latest release of Baidu Intelligent Cloud. It’s time to say it or not, but it’s time to cut down the barriers to digital people’s use in one fell swoop. After hearing about such an artifact, we immediately obtained the qualification for internal testing as usual. Let’s take a sneak peek at more details~ In 5 minutes in one sentence, the 3D digital man will be directly on duty.
- AI 1022 2024-05-08 20:10:39
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- Low-quality multi-modal data fusion, multiple institutions jointly published a review paper
- The AIxiv column is a column where this site publishes academic and technical content. In the past few years, the AIxiv column of this site has received more than 2,000 reports, covering top laboratories from major universities and companies around the world, effectively promoting academic exchanges and dissemination. If you have excellent work that you want to share, please feel free to contribute or contact us for reporting. Submission email: liyazhou@jiqizhixin.com; zhaoyunfeng@jiqizhixin.com Multimodal fusion is one of the basic tasks in multimodal intelligence. The motivation of multi-modal fusion is to jointly utilize effective information from different modalities to improve the accuracy and stability of downstream tasks. Traditional multi-modal fusion methods often rely on high-quality data and are difficult to adapt to real-world applications.
- AI 1140 2024-05-08 19:40:27
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- Green Intelligence: AI-driven innovation in global environmental solutions
- As we seek to overcome the pressing environmental challenges of today’s world, artificial intelligence (AI) stands out as a transformative force. Artificial intelligence-driven technologies known as "green intelligence" are not only reshaping the way we address pollution, waste management and natural resource conservation globally, but are in the process of revolutionizing this approach. By harnessing the power of artificial intelligence, we can analyze massive data sets, predict environmental risks, and implement solutions with unprecedented precision and speed. The implementation of this technology is proving to be critical in our pursuit of a more sustainable and resilient future, allowing us to more effectively respond to the planet's most critical problems. When we adopt artificial intelligence to address environmental challenges, we not only improve today’s applications
- AI 921 2024-05-08 17:55:30
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- In 2024, will there be substantial breakthroughs and progress in end-to-end autonomous driving in China?
- Not everyone can understand that Tesla V12 has been launched on a large scale in North America and has gained recognition from more and more users due to its excellent performance. End-to-end autonomous driving has also become the technical direction that everyone is most concerned about in the autonomous driving industry. Recently, I had the opportunity to have some exchanges with first-class engineers, product managers, investors, and media people in many industries. I found that everyone is very interested in end-to-end autonomous driving, but even in terms of some basic understanding of end-to-end autonomous driving, There are still misunderstandings of this kind. As someone who has been fortunate enough to experience the city function with and without images from a domestic first-tier brand, as well as the two versions of FSD V11 and V12, here I would like to talk about a few things at this stage based on my professional background and tracking the progress of Tesla FSD over the years.
- AI 794 2024-05-08 14:49:12
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- How will fiber optic networks keep up with artificial intelligence?
- As artificial intelligence capabilities continue to develop, the need for powerful fiber optic networks is becoming increasingly urgent. The technology landscape is evolving rapidly, with artificial intelligence and machine learning workloads driving unprecedented demand for connectivity infrastructure. With the advent of the artificial intelligence era, enterprise operating models and the way they interact with data are undergoing subtle changes. Technological advancements have highlighted the importance of fiber optic networks, which are known for their unique bandwidth capabilities and low latency and have become the mainstream of enterprise network architecture. Fiber optic networks have become the core of modern communication systems, supporting the massive data demands of artificial intelligence applications. Benefits of Integrating Artificial Intelligence and Fiber Optic Networks The relationship between AI and fiber optic networks is mutually beneficial, thus driving the advancement of each other. As artificial intelligence applications become
- AI 547 2024-05-08 14:30:02
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- How will fiber optic networks keep up with artificial intelligence?
- The technology landscape is evolving rapidly, with artificial intelligence and machine learning workloads driving the need for connectivity infrastructure. With the advent of the artificial intelligence era, the industry is facing changes. Reorganizing the way enterprises operate and interact with data has become a significant highlight of technological progress. The importance of fiber optic networks is becoming increasingly important, and fiber optic networks are known for their excellent carrying capacity and low latency. Fiber optic networks have become the core of modern communication systems, supporting the massive data demands of artificial intelligence applications. Benefits of Integrating Artificial Intelligence and Fiber Optic Networks The interrelationship between AI and fiber optic networks is mutually beneficial and therefore drives the advancement of each other. As AI applications become more complex and data-intensive, the need for robust fiber optic infrastructure continues to grow. In contrast, fiber optic network speeds and
- AI 1027 2024-05-08 13:40:11
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- Take a look at the past and present of Occ and autonomous driving! The first review comprehensively summarizes the three major themes of feature enhancement/mass production deployment/efficient annotation.
- Written above & The author’s personal understanding In recent years, autonomous driving has received increasing attention due to its potential in reducing driver burden and improving driving safety. Vision-based three-dimensional occupancy prediction is an emerging perception task suitable for cost-effective and comprehensive investigation of autonomous driving safety. Although many studies have demonstrated the superiority of 3D occupancy prediction tools compared to object-centered perception tasks, there are still reviews dedicated to this rapidly developing field. This paper first introduces the background of vision-based 3D occupancy prediction and discusses the challenges encountered in this task. Next, we comprehensively discuss the current status and development trends of current 3D occupancy prediction methods from three aspects: feature enhancement, deployment friendliness, and labeling efficiency. at last
- AI 502 2024-05-08 11:40:01
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- The importance of 5G for manufacturing robots
- The use of robots is often associated with the pursuit of efficiency and productivity. According to the International Trade Administration, a 1% increase in robot density increases productivity by 0.8% across all industries. Today, robotics in manufacturing is the highlight of this ongoing story. Robots are now used at every stage of the manufacturing process in all industries. While robotics is not new in manufacturing, the use of these technologies has exploded in recent years. In the early days of robotics, it was primarily large manufacturers such as automakers that used mobile robots and painting robots for tasks such as painting. However, the rapidly changing business environment has led to a dramatic increase in the adoption of robotics in manufacturing by companies of all sizes. Amount of adoption of robotics in manufacturing
- AI 924 2024-05-08 09:10:07
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