72 citations · 85 across the 9 of their papers we have counts for
9 papers
RoDyn-SLAM: Robust Dynamic Dense RGB-D SLAM with Neural Radiance Fields
Haochen Jiang, Yueming Xu, Kejie Li +2
Leveraging neural implicit representation to conduct dense RGB-D SLAM has been studied in recent years. However, this approach relies on a static environment assumption and does no…
ObjectSDF++: Improved Object-Compositional Neural Implicit Surfaces
Qianyi Wu, Kaisiyuan Wang, Kejie Li +2
In recent years, neural implicit surface reconstruction has emerged as a popular paradigm for multi-view 3D reconstruction. Unlike traditional multi-view stereo approaches, the neu…
MVDream: Multi-view Diffusion for 3D Generation
Yichun Shi, Peng Wang, Jianglong Ye +3
We introduce MVDream, a diffusion model that is able to generate consistent multi-view images from a given text prompt. Learning from both 2D and 3D data, a multi-view diffusion mo…
Physically Plausible 3D Human-Scene Reconstruction from Monocular RGB Image using an Adversarial Learning Approach
Sandika Biswas, Kejie Li, Biplab Banerjee +2
Holistic 3D human-scene reconstruction is a crucial and emerging research area in robot perception. A key challenge in holistic 3D human-scene reconstruction is to generate a physi…
Contextualising Implicit Representations for Semantic Tasks
Theo W. Costain, Kejie Li, Victor A. Prisacariu
Prior works have demonstrated that implicit representations trained only for reconstruction tasks typically generate encodings that are not useful for semantic tasks. In this work,…
MobileBrick: Building LEGO for 3D Reconstruction on Mobile Devices
Kejie Li, Jia-Wang Bian, Robert Castle +2
High-quality 3D ground-truth shapes are critical for 3D object reconstruction evaluation. However, it is difficult to create a replica of an object in reality, and even 3D reconstr…
Neural Refinement for Absolute Pose Regression with Feature Synthesis
Shuai Chen, Yash Bhalgat, Xinghui Li +4
Absolute Pose Regression (APR) methods use deep neural networks to directly regress camera poses from RGB images. However, the predominant APR architectures only rely on 2D operati…
NoPe-NeRF: Optimising Neural Radiance Field with No Pose Prior
Wenjing Bian, Zirui Wang, Kejie Li +2
Training a Neural Radiance Field (NeRF) without pre-computed camera poses is challenging. Recent advances in this direction demonstrate the possibility of jointly optimising a NeRF…
Object-Compositional Neural Implicit Surfaces
Qianyi Wu, Xian Liu, Yuedong Chen +4
The neural implicit representation has shown its effectiveness in novel view synthesis and high-quality 3D reconstruction from multi-view images. However, most approaches focus on…