activity
20212024
most citedTowards Visual Foundational Models of Physical Scenes

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV20231 cited

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 "…

cs.RO2021

Fast Direct Stereo Visual SLAM

Jiawei Mo, Md Jahidul Islam, Junaed Sattar

We propose a novel approach for fast and accurate stereo visual Simultaneous Localization and Mapping (SLAM) independent of feature detection and matching. We extend monocular Dire…