Abstract: A method for distributing an equity reward for federated learning based on an equity theory includes the following steps: applying Adams' equity theory to federated learning, analyzing, by a participant, all factors invested in a federated task comprehensively, then giving an expected reward for this task, calculating, by the task publisher, the reputation of the participant; participating, by the participant, in each round of a training task using a local data to evaluate data contribution, model contribution, and a waiting-time allowance of the participant, then combining contribution results of the three factors to evaluate the contribution of the participant; after a global model converges, dynamically adjusting weights of the three factors according to an objective function of the equity reward, with a goal that an actual reward of the participant is as close as possible to the expected reward, and obtaining and distributing the actual reward of the participant.

Abstract: A scene generation method is disclosed, which comprises: controlling, according to an execution request for a target scene, a vehicle to enter a safety preparation state for implementing the target scene (S101); analyzing a script of the target scene, to generate a scene execution strategy for a respective scene execution component of the vehicle (S102), wherein the scene execution strategy includes an execution function and execution time information of the respective scene execution component; and triggering the respective scene execution component to work according to the scene execution strategy, to generate the target scene (S103). A scene generation apparatus, system and device as well as a storage medium are disclosed. According to the method, under the condition of ensuring safety and controllability of the vehicle, more diverse scenes are provided to a user on the vehicle side, and the entertainment and application experience of the vehicle are improved.

Abstract: Provided are a method and apparatus for generating a three-dimensional model. The method includes following. A first image containing a first face is acquired. First point cloud data including contour information of the first face is determined based on the first image. First albedo information of the first face and second point cloud data including detail information of the first face are determined based on the first point cloud data and the first image. A three-dimensional model of the first face is generated based on the first albedo information and the second point cloud data.

Abstract: A recessed downlight with flexible installation structure includes a mounting plate provided with an installation hole and a heat dissipation housing; the downlight installation structure further comprises an introducing module and a guiding structure; the introducing module is arranged on an inner edge of the installation hole and is fixedly connected to the mounting plate; the heat dissipation housing is provided with a guiding structure, and the guiding structure is configured to surround the outer edge of the heat dissipation housing; when the heat dissipation housing is arranged in the installation hole in a penetrating manner, the guiding structure is connected to the introducing module in a paired manner, thereby enabling the heat dissipation housing to be movably arranged on the mounting plate; an LED module with adjustable angle is arranged in the heat dissipation housing.

Abstract: Provided are a method and apparatus for generating a three-dimensional model. The method includes following. A first image containing a first face is acquired. First point cloud data including contour information of the first face is determined based on the first image. First albedo information of the first face and second point cloud data including detail information of the first face are determined based on the first point cloud data and the first image. A three-dimensional model of the first face is generated based on the first albedo information and the second point cloud data.