Abstract: A computing system performs balanced power management based on requirements of graphics scenes in a video game. Based on the requirements of the graphics scenes, the system selects one or more performance metrics to reduce in real-time, where the performance metrics are indicators of video game quality. The system compares estimated power consumption with a power budget after reducing the one or more performance metrics. Based on the requirements of the graphics scenes, the system further selects one or more quality enhancers to activate in real-time while keeping the estimated power consumption within the power budget. Each quality enhancer enhances the video game with respect to a performance metric. The system then displays the video game enhanced by the one or more quality enhancers.

Abstract: A frame interpolation method generates an interpolated frame that is temporally between a first frame and a second frame. A first and a second interpolated frames are generated using motion vectors from a first motion estimator and a second motion estimator, respectively. A weighting map is generated based on indications from the first motion estimator. First pixel locations and second pixel locations in the weighting map are assigned weight values of 1 and 0, respectively. A weighted combination is calculated using the weighting map to produce the interpolated frame output, which includes the first pixel locations from the first interpolated frame and the second pixel locations from the second interpolated frame. The first and the second motion estimators may be an optical flow estimator and the game engine renderer, respectively. Alternatively, the first and the second motion estimators may be the game engine renderer and the optical flow estimator, respectively.

Abstract: A computing system performs artificial-intelligence (AI) super-resolution (SR). The computing system includes multiple processors, which further includes a graphics processing unit (GPU) and an AI processing unit (APU). The computing system also includes a memory to store AI models. When detecting an indication that the loading of the GPU exceeds a threshold, the processors reduce the resolution of a video output from the GPU in response to the indication. One of the AI models is selected based on graphics scenes in the video and the respective power consumption estimates of the AI models. The processors then perform AI SR operations on the video using the selected AI model to restore the resolution of the video for display.

Abstract: An image processing method for a game loop of a game, wherein the game loop comprises a game rendering module and a MEMC module, and is executed by more than one processing unit to generate an output image to display. The image processing method includes rendering, by the game rendering module, a scene of the game to obtain a first image; rendering, by the game rendering module, a UI to obtain a second image; applying, by the MEMC module, MEMC to the first image to generate an interpolated first image; and blending, by the MEMC module, the second image and the interpolated first image into the output image.

Abstract: An electronic device and an input method editor window adjustment method thereof are provided. The electronic device comprises a touch screen and a processor, wherein the touch screen is electrically connected to the processor. The processor is configured to display an input method editor window, wherein the transparency of the input method editor window is a first transparency percentage. The processor increases the transparency of the input method editor window until the transparency reaches a second transparency percentage after an input silence time, wherein the second transparency percentage is smaller than 100%.