2D Human pose estimation (HPE) has been widely used in the many fields such as behavioral understanding, identity authentication, and industrial automatic manufacturing. Most of the previous studies have encountered many constraints, such as restricted scenarios and strict inputs. To solve this problem, we present a simple yet effective HPE network called limb direction cues-aware network (LDCNet) with limb direction cues and differentiated Cauchy labels, which can efficiently suppress uncertainties and prevent deep networks from over-fitting uncertain keypoint positions. In particular, LDCNet...