Deep Learning

ICCV23: SPIN – Lightweight Image Super-Resolution Network Combining Superpixel Clustering and Transformers

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ICCV23: SPIN - Lightweight Image Super-Resolution Network Combining Superpixel Clustering and Transformers

↑ ClickBlue Text Follow the Jishi PlatformAuthor | Yumu Linfeng Source | AICV and Frontiers Editor | Jishi Platform Jishi Introduction The article proposes a new Superpixel Token Interaction Network (SPIN). This method uses superpixels to cluster locally similar pixels, forming interpretable local regions and achieving local information interaction through attention within superpixels. >> Join … Read more

Efficient Neural Network Architecture for Mobile Applications

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Efficient Neural Network Architecture for Mobile Applications

↑ ClickBlue TextFollow the Jishi platformAuthor丨Pai Pai XingSource丨CVHub Jishi Introduction This article presents a simple yet efficient modern inverted residual mobile module designed for mobile applications. The proposed efficient model (Efficient MOdel, EMO) achieves excellent overall performance on the ImageNet-1K, COCO2017, and ADE20K benchmarks, surpassing the SOTA models based on CNN/Transformer at the same computational … Read more

Accelerating Development of AI Computing Power Scenarios: How NPU Breaks Through?

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Accelerating Development of AI Computing Power Scenarios: How NPU Breaks Through?

The popularity of large-scale language models like ChatGPT and GPT-4 has quickly ignited public enthusiasm for artificial intelligence, drawing strong attention from the industry towards AI chips. Compared to general-purpose chips like CPUs and GPUs, NPUs (Neural Processing Units) can handle AI workloads with simpler control flows, higher efficiency, and lower power consumption. With the … Read more

Why AI PCs Need a Powerful NPU?

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Why AI PCs Need a Powerful NPU?

NPU and heterogeneous computing take the lead? Author| Zhou Ya Image| Midjourney Today’s technological era resembles the .com world over 20 years ago. When the internet emerged, there were voices proclaiming that “every computer would connect to the internet,” and now, the same voices are emerging around personal computers (PC), with the keyword being AI. … Read more

Multi-HMR: Multi-Person Whole-Body Human Mesh Recovery

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Multi-HMR: Multi-Person Whole-Body Human Mesh Recovery

Introduction This article is an interpretation of the paper Multi-HMR: Multi-Person Whole-Body Human Mesh Recovery in a Single Shot by VCC student Yu Tao. This work comes from the European NAVER laboratory and has been published at the top computer vision conference ECCV 2024. Project homepage: https://europe.naverlabs.com/blog/whole-body-human-mesh-recovery-of-multiple-persons-from-a-single-image/This work proposes a method called Multi-HMR to recover … Read more

Multi-Token Prediction (MTP) in V3: Inference Acceleration

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Multi-Token Prediction (MTP) in V3: Inference Acceleration

Last time we discussed the structure of the Deepseek model. Today, I will share the inference acceleration tool in V3, the multi-token prediction (MTP) module, which is somewhat similar to speculative decoding, but the specific code has not been open-sourced. Speculative decoding was introduced in a series of articles on inference optimization, which essentially changes … Read more

FPGA: The Next Generation Robot Perception Processor

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FPGA: The Next Generation Robot Perception Processor

Author Introduction: Liu Shaoshan, co-founder of PerceptIn. PhD in Computer Science from the University of California, Irvine, with research interests in intelligent perception computing, system software, architecture, and heterogeneous computing (FPGA, GPU). Currently, PerceptIn focuses on core SLAM technology for augmented reality, virtual reality, and robotics, as well as its implementation and optimization on smart … Read more

Latest Overview of Global Autonomous Driving AI Chips

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Latest Overview of Global Autonomous Driving AI Chips

Click the “Computer Vision Life” above and select “Star”. Quickly obtain the latest insights. 1. Introduction The intelligence of autonomous vehicles depends on algorithms, leading to the emergence and popularity of the concept of software-defined vehicles. However, to realize software-defined vehicles, a hardware computing platform or domain controller capable of supporting highly intelligent and computationally … Read more

Hailo’s Deep Learning Chips: Turbocharging Data Processing for Autonomous Vehicles

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Hailo's Deep Learning Chips: Turbocharging Data Processing for Autonomous Vehicles

By | Dazhuang Lv Reported by AI-Drive AI-Drive Note: The autonomous driving industry is not just about the few leading giants! Recently, Israeli AI startup Hailo Technologies completed a Series A funding round, raising $12.5 million. This funding will be used for the development of deep learning chips to help edge computing devices perform real-time … Read more

Predicting Chromatin Accessibility in Drosophila Using CNN and Multi-Head Attention

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Predicting Chromatin Accessibility in Drosophila Using CNN and Multi-Head Attention

Chromatin accessibility (open chromatin accessibility) has gained increasing attention in the context of gene regulation and evolution, but our understanding of it remains limited. There is particularly little knowledge about how chromatin accessibility develops and evolves. Recently, the Zhao Li laboratory at The Rockefeller University published a research paper titled The evolution and mutational robustness … Read more