Despite the great success in 2D editing using user-friendly tools, such as Photoshop,
semantic strokes, or even text prompts, similar capabilities in 3D areas are still limited, either …

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 …

Existing neural field representations for 3D object reconstruction either (1) utilize object-level
representations, but suffer from low-quality details due to conditioning on a global latent …

Reconstructing objects from real world data and rendering them at novel views is critical to
bringing realism, diversity and scale to simulation for robotics training and testing. In this …

Monocular 3D reconstruction for categorical objects heavily relies on accurately perceiving
each object's pose. While gradient-based optimization in a NeRF framework updates the …

Sparse view 3D reconstruction has attracted increasing attention with the development of
neural implicit 3D representation. Existing methods usually only make use of 2D views …

This paper presents a method, namely NeuS-PIR, for recovering relightable neural surfaces
using pre-integrated rendering from multi-view images or video. Unlike methods based on …

No augmented application is possible without animated humanoid avatars. At the same
time, generating human replicas from real-world monocular hand-held or robotic sensor …

Monocular 3D reconstruction for categorical objects heavily relies on accurately perceiving
each object's pose. While gradient-based optimization within a NeRF framework updates …

With the recent advances in hardware and rendering techniques, 3D models have emerged
everywhere in our life. Yet creating 3D shapes is arduous and requires significant …