Рет қаралды 84
In this video, I talk about state-of-the-art deep learning techniques for human pose estimation, exploring various models like the Stacked Hourglass Network and BlazePose. I discuss how these architectures are structured, from downsampling and upsampling stages to the multi-branch architecture in BlazePose. We also discuss the evolution of key frameworks, such as MobileNetV2's inverted residuals and efficient feature map handling.