Cross-View Panorama Image Synthesis

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 views is not trivial. In this paper, we attempt to solve the novel problem of cross-vi...

Image-based View Synthesis

We present a new method for rendering novel images of exible 3D objects from a small number of example images in correspondence. The strength of the method is the ability to synthesize images whose viewing position is signi cantly far away from the viewing cone of the example images (\view extrapolation"), yet without ever modeling the 3D structure of the scene. The method relies on synthesizin...

Image Based View Synthesis

This dissertation deals with the image-based approach to synthesize a virtual scene using sparse images or a video sequence without the use of 3D models. In our scenario, a real dynamic or static scene is captured by a set of un-calibrated images from different viewpoints. After automatically recovering the geometric transformations between these images, a series of photo-realistic virtual view...

View Interpolation by Image Synthesis

Image Based View Localization System Retrieving from a Panorama Database by SURF

We propose a system for estimating a user’s view direction with its location of a captured image by retrieving its corresponding region from panoramas in a database. In our database, 104 panoramas captured within a local area are stored. For retrieving a user’s location, the query image captured by the user’s planarprojection camera is compared with all the panoramas in the database. SURF is us...