Key to automatically generate natural scene images is to properly arrange among various spatial elements, especially in the depth direction. To this end, we introduce a novel depth structure preserving scene image generation network (DSP-GAN), which favors a hierarchical and heterogeneous architecture, for the purpose of depth structure preserving scene generation. The main trunk of the propose...

Natural scene luminance distributions typically have positive skew, and for single objects, there is evidence that higher skew is a correlate (but not a guarantee) of glossiness. Skewness is also relevant to aesthetics: preference for glossy single objects (with high skew) has been shown even in infants, and skewness is a good predictor of fruit freshness. Given that primate vision appears to e...

Recursive structure is commonly found in the inputs of different modalities such as natural scene images or natural language sentences. Discovering this recursive structure helps us to not only identify the units that an image or sentence contains but also how they interact to form a whole. We introduce a max-margin structure prediction architecture based on recursive neural networks that can s...

Recognizing text in natural scene images refers to the problem of identifying words that present on it. Scene text recognition is very difficult due to some reasons such as, images contain very little amount of linguistic context, interpreting versions of letters and digits are required for scene text recognition and also scene text can appear in any orientation. Most of the existing works are ...

Generally, the images captured by Camera has many different shapes, sizes, colours, text, non-text etc regions which very complex the Camera-based scene images usually have background which is very complex. The existing system is very sensitive to font scale changes and background interference with low accuracy. The most important aim of this system is based on character recognition method. Sep...