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高坤, 李汪根, 束阳, 葛英奎, 王志格(安徽师范大学计算机与信息学院)

摘 要
Lightweight high-resolution human pose estimation combined with densely connected networks

gaokun, liwanggen, shuyang, geyingkui, wangzhige(School of Computer and Information,Anhui Normal University)

Human pose estimation is a technology that can be widely used in life. In recent years, many excellent high-precision methods have been proposed, but they are often accompanied by very large model scale, which will encounter the problem of computing power bottleneck in application. Whether for model training or deployment, large models require a lot of computing power as the basis. Most of them have low computing power. Similarly, for the scenes in daily life, the equipment needs more applicability and detection speed of the model, which is difficult to achieve by large models. Because of such requirements, lightweight human pose estimation has become a hot research field. The main problem is how to achieve higher detection accuracy and faster detection speed under the extremely limited number of resources. Lightweight models will inevitably fall into a disadvantage in detection accuracy compared with large models, but fortunately, from many studies in recent years, the lightweight model can also achieve higher detection accuracy. A good balance can be reached between them.