International audienceImage-based rendering (IBR) techniques allow capture and display of 3D environments using photographs. Modern IBR pipelines reconstruct proxy geometry using multi-view stereo, reproject the photographs onto the proxy and blend them to create novel views. The success of these methods depends on accurate 3D proxies, which are difficult to obtain for complex objects such as trees and cars. Large number of input images do not improve reconstruction proportionally; surface extraction is challenging even from dense range scans for scenes containing such objects. Our approach does not depend on dense accurate geometric reconstruction; instead we compensate for sparse 3D information by variational image warping. In particular, we formulate silhouette-aware warps that preserve salient depth discontinuities. This improves the rendering of difficult foreground objects, even when deviating from view interpolation. We use a semi-automatic step to identify depth discontinuities and extract a sparse set of depth constraints used to guide the warp. Our framework is lightweight and results in good quality IBR for previously challenging environments
