4 citations · 10 across the 10 of their papers we have counts for
10 papers
Grounded Compositional and Diverse Text-to-3D with Pretrained Multi-View Diffusion Model
Xiaolong Li, Jiawei Mo, Ying Wang +7
In this paper, we propose an effective two-stage approach named Grounded-Dreamer to generate 3D assets that can accurately follow complex, compositional text prompts while achievin…
Fast Sparse View Guided NeRF Update for Object Reconfigurations
Ziqi Lu, Jianbo Ye, Xiaohan Fei +4
Neural Radiance Field (NeRF), as an implicit 3D scene representation, lacks inherent ability to accommodate changes made to the initial static scene. If objects are reconfigured, i…
A Quantitative Evaluation of Score Distillation Sampling Based Text-to-3D
Xiaohan Fei, Chethan Parameshwara, Jiawei Mo +5
The development of generative models that create 3D content from a text prompt has made considerable strides thanks to the use of the score distillation sampling (SDS) method on pr…
Towards Visual Foundational Models of Physical Scenes
Chethan Parameshwara, Alessandro Achille, Matthew Trager +7
We describe a first step towards learning general-purpose visual representations of physical scenes using only image prediction as a training criterion. To do so, we first define "…
Single View Physical Distance Estimation using Human Pose
Xiaohan Fei, Henry Wang, Xiangyu Zeng +3
We propose a fully automated system that simultaneously estimates the camera intrinsics, the ground plane, and physical distances between people from a single RGB image or video ca…
An Adaptive Framework for Learning Unsupervised Depth Completion
Alex Wong, Xiaohan Fei, Byung-Woo Hong +1
We present a method to infer a dense depth map from a color image and associated sparse depth measurements. Our main contribution lies in the design of an annealing process for det…
Unsupervised Depth Completion from Visual Inertial Odometry
Alex Wong, Xiaohan Fei, Stephanie Tsuei +1
We describe a method to infer dense depth from camera motion and sparse depth as estimated using a visual-inertial odometry system. Unlike other scenarios using point clouds from l…
Geo-Supervised Visual Depth Prediction
Xiaohan Fei, Alex Wong, Stefano Soatto
We propose using global orientation from inertial measurements, and the bias it induces on the shape of objects populating the scene, to inform visual 3D reconstruction. We test th…
Visual-Inertial Object Detection and Mapping
Xiaohan Fei, Stefano Soatto
We present a method to populate an unknown environment with models of previously seen objects, placed in a Euclidean reference frame that is inferred causally and on-line using mon…
A Simple Hierarchical Pooling Data Structure for Loop Closure
Xiaohan Fei, Konstantine Tsotsos, Stefano Soatto
We propose a data structure obtained by hierarchically averaging bag-of-word descriptors during a sequence of views that achieves average speedups in large-scale loop closure appli…