3D Flow Field Facial Reenactment for Identity Preservation
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Solution Overview
Problem
Existing generative AI techniques for facial reenactment struggle with capturing fine-grained details and maintaining visual identity under large pose and expression variations, leading to unrealistic results and rendering artifacts.
Innovation Solution
An image generation model integrating 2D and 3D methodologies, using 3D flow fields for warping and adaptive instance normalization, with U-shaped network refinement and cyclic warp loss to ensure accurate facial expression transfer and background preservation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing generative AI techniques are used for facial reenactment, then motion transfer is achieved, but fine-grained details are lost and visual identity is not preserved under large pose variations
Solution Approach 1:
The patent transitions from 2D image space to 3D latent space by encoding source and target images into three-dimensional latent representations. This dimensional transformation enables the model to capture fine-grained facial details while preserving visual identity, as the 3D space provides additional structural information that maintains subject characteristics under large pose and expression variations.
Solution Approach 2:
The patent introduces a 3D flow field as an intermediary between the source image and target image in latent space. This flow field, represented as a three-dimensional vector field, serves as a mediator that guides the transformation of appearance features while preserving fine-grained details and visual identity, resolving the contradiction between motion transfer and detail preservation.
2Reliability
If 3D flow field warping is applied, then visual identity is preserved under large pose variations, but computational complexity increases
Solution Approach 1:
The patent performs preliminary encoding of source and target images into 3D latent representations before the warping operation. By pre-processing the images in this structured 3D space, the subsequent flow field-based warping becomes more efficient, as it operates on compressed latent features rather than full-resolution images, reducing computational complexity while maintaining visual identity preservation.
Solution Approach 2:
The patent transforms the image representation from 2D pixel space to 3D latent space, changing the fundamental parameters of the data structure. This parameter transformation enables more efficient computation of the flow field, as the 3D latent representations capture essential facial structures with fewer parameters, reducing the computational burden of warping operations.
3Measurement precision
If appearance features are warped using 3D flow field, then target motion is accurately transferred, but rendering artifacts may occur
Solution Approach 1:
The patent incorporates a feedback mechanism where the warped appearance features in 3D latent space are decoded back to 2D image space and compared with the target image. This feedback loop allows the model to adjust the warping operation to minimize rendering artifacts while maintaining accurate motion transfer, as the decoded image provides visual feedback on the quality of the transformation.
Data Source
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AI summary
An image generation system may receive a source image including a source object having appearance features. The appearance features may include unique visual characteristics indicative of a visual identity of the source object. The image generation system may receive a target image including a target object having a target motion. The image generation system may generate, based on the appearance features and the target motion, a three-dimensional (3D) flow field indicative of spatial transformations between the appearance features and the target motion. The image generation system may warp, using the 3D flow field, the appearance features to generate a warped image including a warped object having warped appearance features that mimic the target motion and preserve the visual identity of the source object. The image generation system may provide the warped image as an output image.