88 citations · 435 across the 13 of their papers we have counts for
16 papers
When LLMs step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models
Xianzheng Ma, Brandon Smart, Yash Bhalgat +14
As large language models (LLMs) evolve, their integration with 3D spatial data (3D-LLMs) has seen rapid progress, offering unprecedented capabilities for understanding and interact…
PoRF: Pose Residual Field for Accurate Neural Surface Reconstruction
Jia-Wang Bian, Wenjing Bian, Victor Adrian Prisacariu +1
Neural surface reconstruction is sensitive to the camera pose noise, even if state-of-the-art pose estimators like COLMAP or ARKit are used. More importantly, existing Pose-NeRF jo…
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…
BNV-Fusion: Dense 3D Reconstruction using Bi-level Neural Volume Fusion
Kejie Li, Yansong Tang, Victor Adrian Prisacariu +1
Dense 3D reconstruction from a stream of depth images is the key to many mixed reality and robotic applications. Although methods based on Truncated Signed Distance Function (TSDF)…
Real-Time Highly Accurate Dense Depth on a Power Budget using an FPGA-CPU Hybrid SoC
Oscar Rahnama, Tommaso Cavallari, Stuart Golodetz +5
Obtaining highly accurate depth from stereo images in real time has many applications across computer vision and robotics, but in some contexts, upper bounds on power consumption c…
Let's Take This Online: Adapting Scene Coordinate Regression Network Predictions for Online RGB-D Camera Relocalisation
Tommaso Cavallari, Luca Bertinetto, Jishnu Mukhoti +2
Many applications require a camera to be relocalised online, without expensive offline training on the target scene. Whilst both keyframe and sparse keypoint matching methods can b…