We present a neural rendering-based method called NeRO for reconstructing the geometry
and the BRDF of reflective objects from multiview images captured in an unknown …

Radiance Fields (RF) are popular to represent casually-captured scenes for new view
synthesis and several applications beyond it. Mixed reality on personal spaces needs …

Recent advancements in 2D diffusion models allow appearance generation on untextured
raw meshes. These methods create RGB textures by distilling a 2D diffusion model, which …

Stereo depth estimation usually struggles to deal with textureless scenes for both traditional
and learning-based methods due to the inherent dependence on image correspondence …

Reflections on glossy objects contain valuable and hidden information about the
surrounding environment. By converting these objects into cameras, we can unlock exciting …

Underwater perception and 3D surface reconstruction are challenging problems with broad
applications in construction, security, marine archaeology, and environmental monitoring …

Existing depth sensors are imperfect and may provide inaccurate depth values in
challenging scenarios such as in the presence of transparent or reflective objects. In this …

Abstract We present NeRSP a Neural 3D reconstruction technique for Reflective surfaces
with Sparse Polarized images. Reflective surface reconstruction is extremely challenging as …

Neural implicit surface reconstruction has achieved remarkable progress recently. Despite
resorting to complex radiance modeling, state-of-the-art methods still struggle with …

The goal of non-line-of-sight (NLOS) imaging is to image objects occluded from the camera's
field of view using multiply scattered light. Recent works have demonstrated the feasibility of …