Application research of 3D virtual interactive technology in interactive teaching of arts and crafts

In the virtual reality teaching of arts and crafts, the uploaded image data often contains a lot of noise, which significantly reduces the quality of uploaded images and seriously affects the teaching effect of interactive teaching of arts and crafts based on virtual reality. For this reason, the research proposes an image denoising model based on convolutional neural network and wavelet transform, which adopts residual neural network structure and batch normalization algorithm, aiming at gradient explosion and gradient disappearance that may be caused by convolutional neural network, And the problem of low training efficiency has been optimized. The results show that when the noise standard deviation is 50, model 1 can achieve the target accuracy with only 82 iterations, while model 2 requires as many as 56 iterations. For images of different types and noise intensities, the average PSNR values of model 1 are 29.3dB, 30.5dB and 28.9dB, respectively. In addition, by applying Model 1 to VR teaching of arts and crafts, the average score of class 1 is 9.3 points higher than that of class 2. The proposed model effectively optimizes the virtual reality teaching process of arts and crafts, and provides a useful contribution to the application of virtual reality in the field of education.