74 citations · 186 across the 16 of their papers we have counts for
5 papers · 1 filter
Putting Humans in a Scene: Learning Affordance in 3D Indoor Environments
Xueting Li, Sifei Liu, Kihwan Kim +3
Affordance modeling plays an important role in visual understanding. In this paper, we aim to predict affordances of 3D indoor scenes, specifically what human poses are afforded by…
NRMVS: Non-Rigid Multi-View Stereo
Matthias Innmann, Kihwan Kim, Jinwei Gu +4
Scene reconstruction from unorganized RGB images is an important task in many computer vision applications. Multi-view Stereo (MVS) is a common solution in photogrammetry applicati…
Neural RGB->D Sensing: Depth and Uncertainty from a Video Camera
Chao Liu, Jinwei Gu, Kihwan Kim +2
Depth sensing is crucial for 3D reconstruction and scene understanding. Active depth sensors provide dense metric measurements, but often suffer from limitations such as restricted…
PlaneRCNN: 3D Plane Detection and Reconstruction from a Single Image
Chen Liu, Kihwan Kim, Jinwei Gu +2
This paper proposes a deep neural architecture, PlaneRCNN, that detects and reconstructs piecewise planar surfaces from a single RGB image. PlaneRCNN employs a variant of Mask R-CN…
Neural Inverse Rendering of an Indoor Scene from a Single Image
Soumyadip Sengupta, Jinwei Gu, Kihwan Kim +3
Inverse rendering aims to estimate physical attributes of a scene, e.g., reflectance, geometry, and lighting, from image(s). Inverse rendering has been studied primarily for single…