29 citations · 76 across the 21 of their papers we have counts for
7 papers · 2 filters
AnyHome: Open-Vocabulary Generation of Structured and Textured 3D Homes
Rao Fu, Zehao Wen, Zichen Liu +1
Inspired by cognitive theories, we introduce AnyHome, a framework that translates any text into well-structured and textured indoor scenes at a house-scale. By prompting Large Lang…
Strata-NeRF : Neural Radiance Fields for Stratified Scenes
Ankit Dhiman, Srinath R, Harsh Rangwani +4
Neural Radiance Field (NeRF) approaches learn the underlying 3D representation of a scene and generate photo-realistic novel views with high fidelity. However, most proposed settin…
DiVa-360: The Dynamic Visual Dataset for Immersive Neural Fields
Cheng-You Lu, Peisen Zhou, Angela Xing +8
Advances in neural fields are enabling high-fidelity capture of the shape and appearance of dynamic 3D scenes. However, their capabilities lag behind those offered by conventional…
HyP-NeRF: Learning Improved NeRF Priors using a HyperNetwork
Bipasha Sen, Gaurav Singh, Aditya Agarwal +3
Neural Radiance Fields (NeRF) have become an increasingly popular representation to capture high-quality appearance and shape of scenes and objects. However, learning generalizable…
Semantic Attention Flow Fields for Monocular Dynamic Scene Decomposition
Yiqing Liang, Eliot Laidlaw, Alexander Meyerowitz +2
From video, we reconstruct a neural volume that captures time-varying color, density, scene flow, semantics, and attention information. The semantics and attention let us identify…
SCARP: 3D Shape Completion in ARbitrary Poses for Improved Grasping
Bipasha Sen, Aditya Agarwal, Gaurav Singh +3
Recovering full 3D shapes from partial observations is a challenging task that has been extensively addressed in the computer vision community. Many deep learning methods tackle th…