5 results about "Texture transfer" patented technology

Mesh simplification reduces the complexity of 3D objects while maintaining visual fidelity. While there are effective techniques for mesh simplification for simple meshes, in actual use cases it may be difficult to simplify more complicated meshes. A technical solution retrieves an initial mesh (e.g. a triangle mesh) and constructs an edge list including physical and virtual edges for the initial mesh. The initial mesh is then decimated by iteratively collapsing the edges, prioritized based on a modified quadric error metric that may combine a memory edge quadric error and a memoryless area quadric error. The technical solution may maintain a correspondence map during the decimating and use it to perform texture transfer after simplification based on the correspondence map.

The application provides an image generation method based on style content adaptive normalized pose guidance, belonging to the technical field of image synthesis, inputting a person image, selecting a source image and a target image in the person image, generating a target person image consistent with the source image style and the same as the target image pose, first, the pose information transfer is performed in advance by using an aligned multi-scale content transfer network to predict a target edge map, which not only retains the texture content but also can relieve the spatial dislocation. Secondly, the source style feature is gradually transferred to the target pose and reasonable arrangement is realized by using a style texture transfer network, which is realized by a style adaptive normalization generator, the source style feature, the target pose and the edge are mapped in the same hidden space, the consistency of the style texture and the content is enhanced by adaptively adjusting the source style and the target pose, so that the source style feature is retained to enhance the texture details of the target generation.

Approaches presented herein can utilize a network that learns to embed three-dimensional (3D) coordinates on a surface of one or more 3D shapes into an aligned two-dimensional (2D) texture space, where corresponding parts of different 3D shapes can be mapped to the same location in a texture image. Alignment can be performed using a texture alignment module that generates a set of basis images for synthesizing textures. A trained network can generate a basis shared by all shape textures, and can predict input-specific coefficients to construct the output texture for each shape as a linear combination of the basis images, then deform the texture to match the pose of the input. Such an approach can ensure alignment of textures, even in situations with at least somewhat limited network capacity. To unwrap shapes of complex structure or topology, a masking network can be utilized that cuts the shape into multiple pieces to reduce the distortion in the 2D mapping.

A method includes determining a symmetry plane that the divides a mesh into a first side and a second side opposite the first side; performing, on the first side of the mesh, a decimation process to generate a decimated first side of the mesh; performing UV reparameterization on the decimated first side of the mesh to generate a first side UV reparameterized mesh; performing texture transfer on the first side UV reparameterized mesh to generate a first side texture image; determining whether the first side texture image exhibits a degree of texture symmetry with the second side of the mesh that satisfies a condition; and based on a determination that the condition is not satisfied, performing a symmetry texture transfer process between a first texture coordinate on the first side and a second texture coordinate on the second side.

Systems and methods are provided for transferring color from a candidate garment not suitable for a virtual try-on experience for a user to a target garment of an image suitable for the virtual try-on experience. The source and target images for transferring color may be determined utilizing an amount of overlap of 3D segmentation masks for a candidate garment depicted in a candidate source image against the target garment depicted in a target image to identify that the candidate garment is suited for color transfer based on the comparison. Color or texture may then be transferred to the target garment based on image data of the identified candidate garment.