Abstract: A large model-based video processing method, device and storage medium in the field of artificial intelligence technology, particularly in the fields of deep learning and large models are disclosed. The specific solution includes: collecting an imitation video made by a user based on a target video; extracting three-dimensional postures of the imitation video using a pre-trained large model based on the imitation video; and performing posture assessment on the imitation video using the pre-trained large model based on the three-dimensional postures of the imitation video and pre-obtained three-dimensional postures of the target video to obtain an assessment result.

Abstract: A method, apparatus, device, and storage medium for transforming a hairstyle are provided. The method may include: determining a face bounding box according to information on face key points of acquired face image; constructing grids according to the face bounding box; deforming, by using an acquired target hairstyle function, edge lines of at least a part of the constructed grids, which comprises the hairstyle, to obtain a deformed grid curve; determining a deformed hairstyle in the face image according to the deformed grid curve.

Abstract: A method of generating a virtual character, an electronic device, and a storage medium. A specific implementation solution includes: determining, in response to a first speech command for adjusting an initial virtual character, a target adjustment object corresponding to the first speech command; determining a plurality of character materials related to the target adjustment object; determining a target character material from the plurality of character materials in response to a second speech command for determining the target character material; and adjusting the initial virtual character by using the target character material, so as to generate a target virtual character.

Abstract: The present disclosure provides a method for training an image editing model, a method for editing an image, apparatuses, a device, a storage medium and a computer program. An implementation plan is: acquiring a training sample set; and performing training steps as follows: selecting a description text sample and an image sample from the training sample set; determining a text direction vector based on the selected description text sample and a predetermined text template; inputting the text direction vector into a mapping network of the image editing model to obtain a bias vector; determining an image direction vector based on the selected image sample and the bias vector; calculating a loss value based on the text direction vector and the image direction vector; and determining, in response to the loss value meeting a threshold condition, that training of the image editing model is completed.

Abstract: A method and apparatus for training a virtual image generating model, a method and apparatus for generating a virtual image, a device, a storage medium, and a computer program product are provided. The method for training a virtual image generating model includes: training a first initial model using a standard image sample set and a random vector sample set as first of sample data, to obtain an image generating model; training a second initial model using a test latent vector sample set and a test image sample set as second sample data, to obtain an image encoding model; training a third initial model using a standard image sample set and a descriptive text sample set as third sample data, to obtain an image editing model; and training a fourth initial model using the third sample data based on the above models, to obtain the virtual image generating model.

Abstract: The disclosure provides a method for generating a virtual image, a device and a storage medium. The method includes: receiving a user's speech command comprising a description of a virtual image to be generated; extracting semantic information of the speech command; and obtaining a virtual image corresponding to the semantic information.

Abstract: Provided are a virtual avatar driving method and apparatus, a device, and a storage medium. The virtual avatar driving method includes: determining reference pose data of each of bone nodes when driving a skinned mesh bone model of a virtual avatar to a target patch model with a same topology; synchronously driving the skinned mesh bone model according to the reference pose data of each of the bone nodes; and updating the reference pose data of each of the bone nodes for subsequently driving the skinned mesh bone model.

Abstract: Provided are a driving method and apparatus of an avatar, a device and a medium. The method includes acquiring the skin weight of each skin vertex associated with the current bone node in the skinned mesh model of the avatar; acquiring target avatar data of the skinned mesh model when a picture to be converted is converted into the avatar; determining the bone driving factor of the skinned mesh model based on the skin weight, basic avatar data of the skinned mesh model and the target avatar data; and driving the skinned mesh model based on a bone driving factor of each bone node.

Abstract: A method, apparatus, device, and storage medium for transforming a hairstyle are provided. The method may include: determining a face bounding box according to information on face key points of acquired face image; constructing grids according to the face bounding box; deforming, by using an acquired target hairstyle function, edge lines of at least a part of the constructed grids, which comprises the hairstyle, to obtain a deformed grid curve; determining a deformed hairstyle in the face image according to the deformed grid curve.

Abstract: Embodiments of a method, an apparatus, a device and a storage medium for an animation interaction are provided. The method may include: receiving a person image sent by a terminal device; then generating a three-dimensional virtual image based on the person image, where the three-dimensional virtual image is similar to a person in the person image; generating animation interactive information, where the animation interactive information includes a sequence of interactive expression frames; and sending the three-dimensional virtual image and the animation interactive information to the terminal device.