Research on Automotive Styling Design Tools Based on Styleformer-M
In order to improve the quality of automotive design images,two specialized datasets were developed,and the existing image generation models were optimized through a multi-scale dilated attention mechanism to better capture the main features and structural details of cars.Firstly,the"WhiteCarSet"and"WhiteCarContour"datasets were created,focusing respectively on the collection of the intrinsic features of the car body and the precise collection of the car contours.Subsequently,the Styleformer image generation model was refined by introducing a multi-scale dilated attention mechanism,which bolstered the model's capability to capture long-range depen-dencies and comprehend the global structure of objects.Ultimately,experimental results across multiple datasets demonstrated that the improved model achieved a significant enhancement in the Fréchet Inception Distance(FID)score,with an increase of up to 15.57％compared to traditional models.Moreover,utilizing our custom-developed datasets under the same enhanced model,Styleformer-M,the FID scores improved by approximately 22.29％over other datasets.
car styling designStyleformer-Mintelligent designdataset
万方数据
维普
