Fig. 1. General structure of multi-task supervised lightweight convolutional neural network

Fig. 2. Structures of various convolution modules. (a) Non-bottleneck-1D; (b) LFBlock; (c) DSBlock; (d) USBlock

Fig. 3. Examples of labels. (a) Original images; (b) edge annotation heat maps; (c) visualization result of semantic segmentation labels

Fig. 4. Visualization results of the proposed network model. (a) Original images; (b) semantic segmentation ground truth maps; (c) semantic segmentation prediction maps of the proposed method; (d) comparison maps between the estimated layouts of the proposed method and the real layouts (green is the estimated layout, red is the real layout)

Table 1. Parameters of the encoder

Table 2. Parameters of the decoder

Table 3. Model performance evaluation

Table 4. Performance comparison of different methods on LSUN dataset