Aiming at the problems of low steganographic capacity, difficult information extraction, and poor security in existing information hiding algorithms, this paper proposes a high capacity information hiding algorithm based on GAN（HCGAN）. For secret information embedding, an Im-Residual structure-based encoder is applied to embed the secret information into the carrier image, avoiding the information loss caused by the feature extraction of the convolution layer. For secret information extraction, a dense structure-based decoder is utilized to extract secret information from the secret image, and feature reuse is used to increase the extraction rate of secret information. In terms of anti-steganalysis, the discriminator based on steganalysis and the encoder based on Im-Residual structure are used for adversarial training to improve the anti-steganalysis ability of the secret image. Experiments show that after adversarial training, HCGAN has a lower steganalysis detection rate at an embedding rate of 2bpp than the WOW and S-UNIWARD algorithms at an embedding rate of 0.4bpp.