Pupil location plays a key role in HumanComputer Interaction. However, due to the noise of reflection, blink and eyelash occlusion, as well as the pupils at the edge of image and blurred due to movement, the accuracy and robustness of pupil center location are reduced, which leads to great difficulties in accurate pupil location. Therefore, this paper proposes a pupil detection and location algorithm based on attention mechanism and cavity convolution. The algorithm is based on the codingdecoding structure of UNet, VGG16 is used in the coding part and dilated convolution is introduced to fully extract features, Attention Gate is added in the decoding part to make the model more robust. Then, the least square method is used to fit the pupil segmentation map output by the network. Finally, the pupil center coordinates are obtained according to the fitted image. The algorithm is verified by 24 data sets that are publicly available. Experiments show that the algorithm can accurately locate the pupil position, and the average detection rate can reach 92.6%.