Start point guiding and seam tracking are impor-tant parts of the robot’s intelligent welding process. However, some start point guiding methods have a large amount of calcu-lation and low accuracy. In addition, due to the large curvature of the curved weld, the problem of visual advance in seam tracking should be solved. Therefore, an efficient and accurate start point guiding and seam tracking method for curve weld is proposed in this article. First, according to the characteristics of structural light of different welds, more efficient and accurate start point detection algorithms are proposed for curve v-groove welds and curve lap welds. The extraction of key characteristic points and the judgment of the relationship between them could achieve efficient weld start point detection, and the reasonable robot speed planning during the start point searching process could improve the accuracy of the start point guiding. Besides, a sliding data queue method with cubic B-spline fitting is proposed to overcome the visual advance problem and achieve accurate seam tracking of curve welds. The sliding data queue method can plan the data queue automatically, and improve the computational efficiency by reducing the amount of data to be processed. Cubic B-spline fitting can reduce the measurement error and eliminate the data fluctuation, so as to obtain a smooth welding trajectory. The experimental results show that the proposed method could achieve efficient and accurate start point guiding and seam tracking of curve v-groove weld and lap weld.