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AssigneeSnap Inc.
InventorsJian Ren, Pavlo Chemerys, Vladislav Shakhrai, Ju Hu, Denys Makoviichuk, Sergey Tulyakov, Junli Cao
Estimating the term…
A neural light field (NeLF) that runs real-time on mobile devices for neural rendering of three dimensional (3D) scenes, referred to as MobileR2L. The MobileR2L architecture runs efficiently on mobile devices with low latency and small size, and it achieves high-resolution generation while maintaining real-time inference for both synthetic and real-world 3D scenes on mobile devices. The MobileR2L has a network backbone including a convolutional layer embedding an input image at a resolution, residual blocks uploading the embedded image, and super-resolution modules receiving the uploaded embedded image and rendering an output image having a higher resolution than the embedded image. The convolution layer generates a number of rays equal to a number of pixels in the input image, where a partial number of the rays is uploaded to the super-resolution modules.
A neural light field (NeLF) for neural rendering of three dimensional (3D) scenes, comprising:
A method of using a neural light field (NeLF) comprising a network backbone and super resolution modules, the network backbone including a convolutional layer and residual blocks, the method comprising:
A non-transitory computer readable medium storing program code, which when executed, is operative to cause a neural light field (NeLF) to perform the steps of:
Dependencies are inferred from the claim text.