8 results about "Face identity" patented technology

The present application relates to the technical field of face image editing, in particular to a kind of face image editing method based on multi-modal interactive module of scribble. Through two-way multi-modal interactive module, cross attention graph is calculated from position dimension and channel dimension respectively, the cross attention graph obtained and scribble vector are used to carry out latent space latent reflection on face image latent vector iterative modification, complete scribble and image target editing position semantic content alignment, and scribble is embedded into corresponding latent space;Through single-path multi-modal interactive module, save the original face identity feature after editing, the texture supplement vector obtained carries out latent space latent reflection on face image latent vector iterative modification, and finally generates face image editing result.The present application can more intuitively and fully express the editing intention of user, realize the real feeling editing effect that meets user's expectation, and the present application has superiority in editing effect, editing real feeling and face identity information saving of face image editing.

The invention relates to the field of biological feature recognition and information security, in particular to a face revocable template protection method based on deep hash. The method comprises the following steps: detecting and aligning an input face image, and extracting and normalizing features; performing projection and symbol quantization to obtain a binary vector with a fixed length; deriving a dimension permutation and index subset by using a user key, and generating a protected template; registration and identification are completed in a protected domain by a Hamming distance; when the template is leaked or needs to be replaced, a new template is regenerated by updating a secret key or an index rule, and template revocation and non-linkability are achieved. The system side only stores the protected template and necessary verification parameters and does not store plaintext images and unprotected features, so that the method is low in calculation overhead, convenient to deploy and suitable for face identity authentication of end-side equipment and a cloud platform.

The present application relates to face identity authentication method based on terminal device legitimacy precondition constraint and related device. Including: face recognition terminal sends device check request including device identification to server; Server generates device key based on master key and device identification, and performs device check using device key; If not pass the check, terminate the authentication; If pass, generate collection permission token through the server, so that the terminal collects face feature data based on the collection permission token, calculates the first message authentication code using the pre-stored authentication material for face feature, device identification and session identification, generates face identity authentication request, and forwards to the server through the client; Through the server, generate device key based on master key and received device identification using key derivation algorithm, and verify the first message authentication code based on the device key, and determine the identity authentication result according to the verification result. The security of identity authentication is improved, and the risk of privacy leakage is reduced.

This invention discloses an image quality enhancement method and system based on face recognition, belonging to the field of image processing technology. The method includes the following steps: acquiring an original low-quality image and obtaining initial localization point coordinates; generating a pre-enhanced image; obtaining refined localization point coordinates; calculating the displacement amplitude based on the displacement vector; obtaining a final set of localization point coordinates; calculating a refined affine transformation matrix based on the final set of localization point coordinates; generating a refined aligned image; and performing subsequent enhancement processing operations using the refined aligned image. This invention solves the problem in existing technologies where the alignment transformation matrix generates systematic deviations, leading to semantic misalignment artifacts and ultimately irreversible shifts in facial identity features. By performing pre-enhancing processing on the original low-quality image and triggering a second round of localization point detection, and then performing weighted fusion coordinate calculation based on anchor point constraints on the initial localization point coordinates, this invention addresses the problem of systematic deviations in the alignment transformation matrix, resulting in semantic misalignment artifacts and ultimately irreversible shifts in facial identity features.

The application relates to a video generation method and system based on face consistency constraints, wherein the method comprises the following steps: generating a reference face image of a target character based on a first prompt word describing only information of the target character; generating and freezing a unique identity Face ID of the target character based on the reference face image; generating a corresponding shot image package based on shot description information corresponding to each shot in a plot text, combining the frozen unique identity Face ID and a second prompt word; generating a corresponding video segment based on each shot image package, and synthesizing final video according to the shot order. Through the application, the Face ID of the reference face image is used to separate the face identity of the character from the video generation process, effectively ensuring the consistency of the identity of the character in the generated video, and each shot of the script is split to generate segments, so that the video generation process is structured, controllable and rollbackable.

This invention provides an active defense method against deepfake face-swapping based on facial identity feature-level perturbation, belonging to the fields of artificial intelligence, digital image processing, and network information security. The method includes: (1) source face image acquisition and preprocessing; (2) facial identity feature extraction; (3) identity feature perturbation generation; (4) protection image reconstruction based on perturbed identity features; (5) adversarial optimization and joint training strategy; and (6) protection face image output and application. This invention, by performing targeted perturbation on facial identity features and reconstructing protection images, weakens the ability of deepfake face-swapping models to extract and utilize source identity features from the root, while ensuring the visual naturalness and consistency of face images. This achieves proactive defense against deepfake face-swapping behavior, solving the core problems of insufficient defense effectiveness, poor robustness in black-box scenarios, and difficulty in balancing defense effect and visual perception in existing technologies.

The present application relates to the field of identity authentication, and particularly relates to a terminal device leasing identity authentication method based on multi-source data verification, comprising: periodically acquiring an authentication trigger risk coefficient of a device leasing target to determine whether to perform authentication analysis processing; when performing authentication analysis processing, determining whether to include trigger auxiliary analysis for the device leasing target according to a stage trigger reference index and a stage trigger highlight index; when performing trigger auxiliary analysis, determining a potential risk trigger index of the device leasing target according to a reference cooperative trend index or a reference evaluation abnormal index, and determining whether to adjust the potential risk trigger index based on a response correlation interval index; when performing trigger authentication analysis, acquiring a trigger execution evaluation coefficient of the device leasing target; and determining whether to trigger face identity authentication according to the trigger execution evaluation coefficient. The present application effectively takes into account the effectiveness of the biological feature authentication trigger decision and the abnormal response efficiency.

The application relates to a face identity protection method and system for three-dimensional Gaussian point cloud scene editing. The method comprises the following steps: acquiring three-dimensional Gaussian point cloud scene data and camera internal and external parameters, generating a scene image through multi-view rendering; detecting a face to obtain a region mask, and projecting two-dimensional face pixels to a three-dimensional space to screen out target Gaussian points related to the identity of a person; performing text-driven image editing based on a diffusion editing model, extracting face features before and after editing to calculate identity consistency loss and visual feature difference loss; generating weights according to the identity leakage degree of each view angle, and obtaining a multi-view identity protection loss through weighted fusion, and the multi-view identity protection loss is combined with a three-dimensional scene editing loss to be optimized, and finally, scene parameters are updated. The method positions target Gaussian points through multi-view face back projection, and combines multi-view weighted identity protection loss to be optimized, so that the face identity protection capability and scene editing security in the Gaussian point cloud scene editing process are significantly improved.