5 citations · 12 across the 6 of their papers we have counts for
14 papers
3D Textured Shape Recovery with Learned Geometric Priors
Lei Li, Zhizheng Liu, Weining Ren +4
3D textured shape recovery from partial scans is crucial for many real-world applications. Existing approaches have demonstrated the efficacy of implicit function representation, b…
Shape As Points: A Differentiable Poisson Solver
Songyou Peng, Chiyu "Max" Jiang, Yiyi Liao +3
In recent years, neural implicit representations gained popularity in 3D reconstruction due to their expressiveness and flexibility. However, the implicit nature of neural implicit…
UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction
Michael Oechsle, Songyou Peng, Andreas Geiger
Neural implicit 3D representations have emerged as a powerful paradigm for reconstructing surfaces from multi-view images and synthesizing novel views. Unfortunately, existing meth…
KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs
Christian Reiser, Songyou Peng, Yiyi Liao +1
NeRF synthesizes novel views of a scene with unprecedented quality by fitting a neural radiance field to RGB images. However, NeRF requires querying a deep Multi-Layer Perceptron (…
Dynamic Plane Convolutional Occupancy Networks
Stefan Lionar, Daniil Emtsev, Dusan Svilarkovic +1
Learning-based 3D reconstruction using implicit neural representations has shown promising progress not only at the object level but also in more complicated scenes. In this paper,…
Convolutional Occupancy Networks
Songyou Peng, Michael Niemeyer, Lars Mescheder +2
Recently, implicit neural representations have gained popularity for learning-based 3D reconstruction. While demonstrating promising results, most implicit approaches are limited t…