4 citations · 11 across the 10 of their papers we have counts for
9 papers · 1 filter
Event-based Photometric Stereo via Rotating Illumination and Per-Pixel Learning
Hyunwoo Kim, Won-Hoe Kim, Sanghoon Lee +3
Photometric stereo is a technique for estimating surface normals using images captured under varying illumination. However, conventional frame-based photometric stereo methods are…
Human Hair Reconstruction with Strand-Aligned 3D Gaussians
Egor Zakharov, Vanessa Sklyarova, Michael Black +3
We introduce a new hair modeling method that uses a dual representation of classical hair strands and 3D Gaussians to produce accurate and realistic strand-based reconstructions fr…
A Local Appearance Model for Volumetric Capture of Diverse Hairstyle
Ziyan Wang, Giljoo Nam, Aljaz Bozic +4
Hair plays a significant role in personal identity and appearance, making it an essential component of high-quality, photorealistic avatars. Existing approaches either focus on mod…
Differentiable Display Photometric Stereo
Seokjun Choi, Seungwoo Yoon, Giljoo Nam +2
Photometric stereo leverages variations in illumination conditions to reconstruct surface normals. Display photometric stereo, which employs a conventional monitor as an illuminati…
Event Fusion Photometric Stereo Network
Wonjeong Ryoo, Giljoo Nam, Jae-Sang Hyun +1
We present a novel method to estimate the surface normal of an object in an ambient light environment using RGB and event cameras. Modern photometric stereo methods rely on an RGB…
NeuWigs: A Neural Dynamic Model for Volumetric Hair Capture and Animation
Ziyan Wang, Giljoo Nam, Tuur Stuyck +6
The capture and animation of human hair are two of the major challenges in the creation of realistic avatars for the virtual reality. Both problems are highly challenging, because…
Neural Strands: Learning Hair Geometry and Appearance from Multi-View Images
Radu Alexandru Rosu, Shunsuke Saito, Ziyan Wang +3
We present Neural Strands, a novel learning framework for modeling accurate hair geometry and appearance from multi-view image inputs. The learned hair model can be rendered in rea…
ORA3D: Overlap Region Aware Multi-view 3D Object Detection
Wonseok Roh, Gyusam Chang, Seokha Moon +5
Current multi-view 3D object detection methods often fail to detect objects in the overlap region properly, and the networks' understanding of the scene is often limited to that of…
HVH: Learning a Hybrid Neural Volumetric Representation for Dynamic Hair Performance Capture
Ziyan Wang, Giljoo Nam, Tuur Stuyck +4
Capturing and rendering life-like hair is particularly challenging due to its fine geometric structure, the complex physical interaction and its non-trivial visual appearance.Yet,…