Search Results for author:
Found 6 papers, 2 papers with code
Gaussian Shell Maps for Efficient 3D Human Generation
Instead of rasterizing the shells directly, we sample 3D Gaussians on the shells whose attributes are encoded in the texture features.
Stanford-ORB: A Real-World 3D Object Inverse Rendering Benchmark
We introduce Stanford-ORB, a new real-world 3D Object inverse Rendering Benchmark.
PaletteNeRF: Palette-based Appearance Editing of Neural Radiance Fields
Recent advances in neural radiance fields have enabled the high-fidelity 3D reconstruction of complex scenes for novel view synthesis.
NeROIC: Neural Rendering of Objects from Online Image Collections
We present a novel method to acquire object representations from online image collections, capturing high-quality geometry and material properties of arbitrary objects from photographs with varying cameras, illumination, and backgrounds.
DenseGAP: Graph-Structured Dense Correspondence Learning with Anchor Points
To make the local features aware of the global context and improve their matching accuracy, we introduce DenseGAP, a new solution for efficient Dense correspondence learning with a Graph-structured neural network conditioned on Anchor Points.
Task-Generic Hierarchical Human Motion Prior using VAEs
We demonstrate the effectiveness of our hierarchical motion variational autoencoder in a variety of tasks including video-based human pose estimation, motion completion from partial observations, and motion synthesis from sparse key-frames.
Ranked #4 on
Motion Synthesis
on LaFAN1
