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Artificial intelligence (AI) systems must understand visual scenes in three dimensions to interpret the world around us. For that reason, images play an essential role in computer vision, significantly affecting quality and performance. Unlike the widely available 2D data, 3D data is rich in scale and geometry information, providing an opportunity for a better machine-environment understanding.
Data-driven 3D modeling, or 3D reconstruction, is a growing computer vision domain increasingly in demand from industries including augmented reality (AR) and virtual reality (VR). Rapid advances in implicit neural representation are also opening up exciting new possibilities for virtual reality experiences.
3D reconstruction generates a 3D object or scene representation by combining a sparse set of images of the object or scene from arbitrary viewpoints. The method allows for accurate reconstruction of shapes with complex geometries, as well as higher color reconstruction.
3D reconstruction in the era of digital reality
With the rise of digital experiences and emerging virtual concepts such as the metaverse, it’s critical to have tools that can create accurate 3D reconstructions from image data. Real-world applications of this technology allows users to virtually try on clothing while shopping in AR and VR, as well as to process medical image data. It can also be used for free-viewpoint video reconstruction, robotic mapping, reverse engineering and even reliving memorable moments from various perspectives. According to a SkyQuest survey, the global 3D reconstruction technology market will be worth $1,300 million by 2027.
3D reconstruction is now a priority by tech and ecommerce giants, as it not only lays the groundwork for a future presence in virtual worlds but also provides immediate tangible business benefits in advertising or social commerce.
Recently, Shopify reported that merchants who add 3D cont …