Three-dimensional Animation Generation and Image Enhancement Technology Based on Multi-Column Convolutional Neural Network Model

This paper aims to improve the quality and fidelity of three-dimensional (3D) animation. Firstly, application model Multi-Column Convolutional Neural Network (MCNN) in 3D animation generation image enhancement is proposed. Aiming at animation, MCNN algorithm suitable for this field selected, its working principle explained detail. Meanwhile, theoretical basis introduced, which provides a subsequent experiments. Secondly, enhancement, also selected as key technology, explained. Finally, simulation experiment carried out evaluate effect proposed enhancement. By collecting appropriate data sets setting parameters corresponding experimental environment, performance evaluated. The results show that, compared with traditional methods, shows better tasks. Specifically, method can still maintain good under conditions shorter training time, faster reasoning time lower memory occupation, has advantages computational efficiency. technology significantly fidelity, satisfactory have been obtained. verify potential provide new ideas directions further research application.