Pixel Wise Pruning

Pixel-wise pruning is a technique focused on improving the efficiency of various image processing and computer vision models by selectively removing less important pixels from input data or model parameters. Current research explores this approach across diverse applications, including 3D scene rendering, image classification, and video super-resolution, often employing neural network architectures and tailored pruning algorithms to optimize for speed and memory usage while minimizing quality loss. This research is significant because it addresses the computational limitations of many advanced image processing tasks, enabling their deployment on resource-constrained devices and improving real-time performance in applications like augmented and virtual reality.