[Retracted] 3D Animation Automatic Generation System Design Based on Deep Learning

Table 1

Feature recognition experimental results of different 3D animation facial expression generation methods.

	Occlusion type	Block body type	Root mean square error	Pearson’s correlation coefficient
Expression generation method based on improved CycleGAN model	Unobstructed	0 × 0	0.018	0.889
	Random block 25%	112 × 112	0.132	0.506
	Random block 50%	120 × 120	0.201	0.489
Expression generation method based on generative adversarial network	Unobstructed	0 × 0	0.305	0.968
	Random block 25%	112 × 112	0.425	0.669
	Random block 50%	120 × 120	0.021	0.589
The proposed expression generation method	Unobstructed	0 × 0	0.001	0.995
	Random block 25%	112 × 112	0.013	0.959
	Random block 50%	120 × 120	0.016	0.978