# Exploring Deep Neural Networks in Simulating Human Vision through Five Optical Illusions
## 3 Results  
### Color Assimilation  
Color assimilation [34] refers to the perceptual changes in the hue of a color square when positioned against various backgrounds. Specifically, when the square is placed against backgrounds comprising black, gray, and white stripes, this leads to distinct variations in color perception. Based on the square's location relative to these backgrounds, it shows three color hues in the base color. Consequently, we have categorized the three positions of the square against the background as depth1, depth2, and depth3, as illustrated in Figure 2A. This section presents participants' perceptual rankings of three distinct color depths (labeled as depth1, depth2, and depth3 in Figure 2A) across a wheel of 12 colors and the DNN performance in ranking these three depths in 12 colors. The data from participants, who observed a square of 12 colors and their corresponding three depths and then ranked the depths, are presented as average frequencies, as shown in Figure 4A, where each depth of the 12 colors corresponds to a specific ranking. These rankings reflect the perceived similarity between the color depth and the original color. A larger number on the axis indicates that the color depth is more similar to the color of the square. The results show that all colors ranked highest at depth2, suggesting that this depth is visually closest to the original color. Overall, the frequency of rankings is primarily concentrated in two configurations: depth (231) and (213). In the color assimilation test involving the 12 models for the 12 colors, we extracted the feature vectors for each primary color and its corresponding color depth from the last convolutional layer of each model. We then calculated their L2 distances to assess their similarity. Based on these similarity data, we also conducted a ranking classification, as shown in Figure 4B. The ranking order presents six different combinations of depth ranking, with each number representing a color depth. Figure 2B shows the distribution of color rankings for each model. According to the high-frequency human rankings depth (231) and (213), only ResNetv2_101 [29] and VGG16 [8] show higher frequencies in these two rankings. In addition, the most frequently occurring ranking across all models is \"312\". We also presented the representational dissimilarity matrix (RDM) [25] heatmaps of 12 models for the 12 colors (Figure 5). The darker the color in the heatmap, the higher the similarity. Each color corresponds to the original color square and its depths from depth1 to depth3, forming a 4 \(\times\) 4 matrix. From the heatmap, it can be observed that ResNet_v2 with \"pre-activation\" architecture exhibits deep red across almost all areas, indicating that this model may not be particularly sensitive to color. Similarly, VGG16, despite its similarity in human perceptual rankings, also displays this characteristic. In contrast, other models within the ResNet series demonstrate more pronounced color differentiation capabilities, especially outside the heatmap's diagonal regions. Among the colors in the high-frequency human ranking depths (231) and (213), green appeared most frequently across the 12 models. We visualized the different depths of green using CAM (class activation mapping) [26; 27] to explore the network's decision-making and feature preferences. As shown in Figure 6, most models focused, to some extent, on the inner color square, but VGG16 and VGG19 were exceptions. ResNext101 [30] focused on the features of the entire square at each color depth. Other models showed a preference for focusing on the features of the square's edges or certain middle areas. Moreover, the most frequently occurring red color also showed a similar pattern across the 12 models (see Figure A1), but with more models tending to focus on the middle area and edges of the square. Additionally, as can be seen from Figure 4C, at the shallow layers (primary modules), all models showed a high frequency of depth (132) ranking.