Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation

Image-to-image translation has been made much progress with embracing Generative Adversarial Networks (GANs). However, it's still very challenging for translation tasks that require high quality, especially at high-resolution and photorealism. In this paper, we present Discriminative Region Proposal Adversarial Networks (DRPAN) for high-quality image-to-image translation. We decompose the procedure of image-to-image translation task into three iterated steps, first is to generate an image with global structure but some local artifacts (via GAN), second is using our DRPnet to propose the most fake region from the generated image, and third is to implement "image inpainting" on the most fake region for more realistic result through a reviser, so that the system (DRPAN) can be gradually optimized to synthesize images with more attention on the most artifact local part. Experiments on a variety of image-to-image translation tasks and datasets validate that our method outperforms state-of-the-arts for producing high-quality translation results in terms of both human perceptual studies and automatic quantitative measures.Comment: ECCV 201

Quasi-regular facade structure extraction

In this paper we present a novel two-stage framework for extracting what we define as a quasi-regular structure in facade images. A quasi-regular structure is an irregular rectangular grid representing the placements of repetitive structural architecture objects, e.g., windows, in a facade. Such a structure generalizes a perfect lattice structure generated by the 2D symmetry groups, studied by the previous work. First, we propose to formulate the quasi-regular structure detection in an object-oriented Marked Point Process framework by treating the architectural elements as objects. This leads to an initial quasi-regular structure map which serves as an indicator map of potential object locations. Then, we propose a regularization scheme to recover the complete quasi-regular structures from the initial incomplete structure. This stage takes advantage of the intrinsic low rank constraint of the quasi-regular structure representing a regularized facade. By applying such a regularization, the complete quasi-regular facade structure is obtained. We have extensively tested our method on a large variety of facade images, and demonstrated both the effectiveness and the robustness of our two-stage framework. © 2013 Springer-Verlag