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• A layout plane is a closed loop surrounded by layout keypoints. • The wall structure can be parametrization as an undirected graph. • Layout keypoint prediction is relative to human pose estimation. • Cuboid room assumption is limited in real life. Room layout estimation aims to predict the spatial structure of a room from a single image. Most existing methods relying on 2D cues are suitable for cuboid rooms, but non-cuboid rooms. 3D layout estimation methods can reconstruct 3D models of general rooms, but they are trained with depth information on high collection costs, consume large computation resources, and run slowly. This paper considers an undirected graph representation method of the general room layouts, which includes cuboid and non-cuboid rooms consisting of a single ceiling, a single floor, and multiple walls. To this end, we first predict the positions of the layout vertices and then use the network automatically learn the connection relationship between the vertices. The final layout is obtained through a simple layout inference post-processing algorithm. The experimental results both on cuboid and non-cuboid datasets validate the effectiveness and efficiency of our method. The code is available at https://github.com/Hui-Yao/2D-graph-layout-estimation. [ABSTRACT FROM AUTHOR]

Nowadays, stereoscopic image quality assessment (SIQA) based on convolutional neural network (CNN) has become the mainstream model of image quality assessment (IQA). Compared with the two-dimensional quality evaluation model, stereoscopic image quality evaluation is more challenging due to the effects of depth and parallax information. In this paper, we propose a two-stream interactive network model to perform quality evaluation, which can well simulate the process of human stereo visual perception. Meanwhile, we enhance the extraction of local and global features of images by asymmetric convolution kernel and interactive sub-networks of inter-layers, respectively, which can further optimize our network model. Our proposed algorithm was evaluated on four public databases. The final experimental results show that our proposed algorithm exhibits good performance not only on the whole database but also on each single distortion type. [ABSTRACT FROM AUTHOR]