Cross-View Image Synthesis using Conditional GANs

Learning to generate natural scenes has always been a challenging task in computer vision. It is even more painstaking when the generation is conditioned on images with drastically different views. This is mainly because understanding, corresponding, and transforming appearance and semantic information across the views is not trivial. In this paper, we attempt to solve the novel problem of cross-view image synthesis, aerial to street-view and vice versa, using conditional generative adversarial networks (cGAN). Two new architectures called Crossview Fork (X-Fork) and Crossview Sequential (X-Seq) are proposed to generate scenes with resolutions of 64x64 and 256x256 pixels. X-Fork architecture has a single discriminator and a single generator. The generator hallucinates both the image and its semantic segmentation in the target view. X-Seq architecture utilizes two cGANs. The first one generates the target image which is subsequently fed to the second cGAN for generating its corresponding semantic segmentation map. The feedback from the second cGAN helps the first cGAN generate sharper images. Both of our proposed architectures learn to generate natural images as well as their semantic segmentation maps. The proposed methods show that they are able to capture and maintain the true semantics of objects in source and target views better than the traditional image-to-image translation method which considers only the visual appearance of the scene. Extensive qualitative and quantitative evaluations support the effectiveness of our frameworks, compared to two state of the art methods, for natural scene generation across drastically different views.Comment: Accepted at CVPR 201

Parametric analysis of the stability of a bicycle taking into account geometrical, mass and compliance properties

Some studies of bicycle dynamics have applied the Whipple Carvallo bicycle model (WCBM) for the stability analysis. The WCBM is limited, since structural elements are assumed to be rigid bodies. In this paper, the WCBM is extended to include the front assembly lateral compliance, and analysis focuses on the study of the open loop stability of a benchmark bicycle. Experimental tests to identify fork and wheel properties are performed, this data is used in the stability analysis for ranking the influence of design parameters. Indexes from the eigenvalues analysis are applied in a full factorial approach. The results show that introducing front assembly compliance generates a wobble mode with little effect on self-stability. The forward displacement of the centre of mass of the rear frame and the increment in trail lead to large increments in the self-stability, whereas increments in front wheel radius and wheelbase reduce stability

Unzipping DNA by force: thermodynamics and finite size behaviour

We discuss the thermodynamic behaviour near the force induced unzipping transition of a double stranded DNA in two different ensembles. The Y-fork is identified as the coexisting phases in the fixed distance ensemble. From finite size scaling of thermodynamic quantities like the extensibility, the length of the unzipped segment of a Y-fork, the phase diagram can be recovered. We suggest that such procedures could be used to obtain the thermodynamic phase diagram from experiments on finite length DNA.Comment: 10 pages, accepted for publication in special issue of Journal of Physics: Condensed Matte