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Ambarella Introduces CV22 4K SoC with CVflow™ Computer Vision Architecture

New CV22 SoC targets intelligent security, automotive, drone and wearable cameras


SANTA CLARA, Calif., Jan 8, 2018 — Ambarella, Inc. (NASDAQ: AMBA) a leading developer of low-power, HD and Ultra HD video processing semiconductors, today introduced the CV22 camera SoC, the second chip in the CVflow family, combining image processing, 4Kp60 video encoding and CVflow computer vision processing in a single, low power design. The CV22’s CVflow architecture provides the DNN (Deep Neural Network) processing required for the next generation of intelligent home monitoring, automotive, drone and wearable cameras. Fabricated in advanced 10nm process technology, it achieves an industry-leading combination of low-power and high-performance in both human vision and computer vision applications. PR26_Ambarella_CV22_2017_18oLogos.png


“CV22 enables customers to deploy cameras with high-performance deep-learning capabilities,” said Fermi Wang, CEO of Ambarella. “Compared with inefficient CPU and GPU solutions, CV22 provides powerful computer vision performance combined with high-quality image processing, efficient video encoding and the low-power operation required to be deployed in mass production. It will enable a new level of intelligence in cameras, ranging from person recognition in home monitoring cameras to advanced ADAS capabilities in automobiles.”


The CV22’s CVflow architecture provides computer vision processing at full 4K or 8-Megapixel resolution at 30 frames per second, to enable image recognition over long distances and with high accuracy. It includes efficient 4K encoding in both AVC and HEVC video formats, delivering high-resolution video streaming with very low bitrates to minimize cloud storage costs. The CV22’s next-generation ISP (Image Signal Processor) provides outstanding imaging in low light conditions while HDR (High Dynamic Range) processing extracts maximum image detail in high contrast scenes, further enhancing the computer vision capabilities of the chip. It includes a suite of advanced security features to prevent hacking, including secure boot, TrustZone™ and I/O virtualization.


A complete set of tools is provided to help customers to easily port their own neural networks onto the CV22 SoC. This includes compiler, debugger and support for industry standard training tools including Caffe™ and TensorFlow™, with extensive guidelines for CNN (Convolutional Neural Network) performance optimizations.


CV22 SoC Key Features:

  • CVflow processor with CNN/deep learning support
  • 4Kp60/8-Megapixel  AVC and HEVC encoding with multi-stream support
  • Quad-core  1.2-GHz ARM™ Cortex A53 with NEON DSP extensions and FPU
  • Advanced security features, including OTP for secure boot, TrustZone and IO virtualization
  • Real-time hardware-accelerated 360-degree de-warping and Lens Distortion Correction (LDC) engine
  • Multi-channel ISP with up to 800-Megapixel/s input pixel rate
  • Multi-exposure HDR and WDR processing 
  • LED flicker mitigation
  • SmartAVC™ and SmartHEVC™ intelligent rate control for lowest bitrates
  • in security applications
  • Multi-sensor support for multi-imager security cameras, 3-channel electronic mirror and 4-channel AVM systems
  • High-speed SLVS/MIPI/LVCMOS interfaces
  • Rich set of interfaces includes GigE Ethernet, CAN bus, USB 2.0 host and device, dual SD card controllers with SDXC support, HDMI v2.0,
  • MIPI-DSI/CSI 4-lane output
  • 10nm process technology
  • Package: 441-pin 0.65-pitch BGA


Pricing and Availability

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About Ambarella

Ambarella, Inc. (NASDAQ: AMBA), is a leading developer of low-power, high-definition (HD) and Ultra HD video compression, image processing and computer vision solutions. The company’s products are used in a variety of IP security, sports, wearable, drone and automotive video cameras. Ambarella’s solutions leverage over 20 years of pioneering research in computer vision to enable future generations of intelligent cameras, Advanced Driver Assistance Systems and autonomous vehicles. For more information about Ambarella, please visit


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