790 citations · 1.5k across the 18 of their papers we have counts for
18 papers · 1 filter
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…
GaussCtrl: Multi-View Consistent Text-Driven 3D Gaussian Splatting Editing
Jing Wu, Jia-Wang Bian, Xinghui Li +4
We propose GaussCtrl, a text-driven method to edit a 3D scene reconstructed by the 3D Gaussian Splatting (3DGS). Our method first renders a collection of images by using the 3DGS a…
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…
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…
SC-DepthV3: Robust Self-supervised Monocular Depth Estimation for Dynamic Scenes
Libo Sun, Jia-Wang Bian, Huangying Zhan +3
Self-supervised monocular depth estimation has shown impressive results in static scenes. It relies on the multi-view consistency assumption for training networks, however, that is…
Unsupervised Scale-consistent Depth Learning from Video
Jia-Wang Bian, Huangying Zhan, Naiyan Wang +5
We propose a monocular depth estimator SC-Depth, which requires only unlabelled videos for training and enables the scale-consistent prediction at inference time. Our contributions…
DF-VO: What Should Be Learnt for Visual Odometry?
Huangying Zhan, Chamara Saroj Weerasekera, Jia-Wang Bian +2
Multi-view geometry-based methods dominate the last few decades in monocular Visual Odometry for their superior performance, while they have been vulnerable to dynamic and low-text…
Diverse Knowledge Distillation for End-to-End Person Search
Xinyu Zhang, Xinlong Wang, Jia-Wang Bian +2
Person search aims to localize and identify a specific person from a gallery of images. Recent methods can be categorized into two groups, i.e., two-step and end-to-end approaches.…
MobileSal: Extremely Efficient RGB-D Salient Object Detection
Yu-Huan Wu, Yun Liu, Jun Xu +3
The high computational cost of neural networks has prevented recent successes in RGB-D salient object detection (SOD) from benefiting real-world applications. Hence, this paper int…
Auto-Rectify Network for Unsupervised Indoor Depth Estimation
Jia-Wang Bian, Huangying Zhan, Naiyan Wang +3
Single-View depth estimation using the CNNs trained from unlabelled videos has shown significant promise. However, excellent results have mostly been obtained in street-scene drivi…
Ordered or Orderless: A Revisit for Video based Person Re-Identification
Le Zhang, Zenglin Shi, Joey Tianyi Zhou +5
Is recurrent network really necessary for learning a good visual representation for video based person re-identification (VPRe-id)? In this paper, we first show that the common pra…
An Evaluation of Feature Matchers for Fundamental Matrix Estimation
Jia-Wang Bian, Yu-Huan Wu, Ji Zhao +4
Matching two images while estimating their relative geometry is a key step in many computer vision applications. For decades, a well-established pipeline, consisting of SIFT, RANSA…
Visual Odometry Revisited: What Should Be Learnt?
Huangying Zhan, Chamara Saroj Weerasekera, Jiawang Bian +1
In this work we present a monocular visual odometry (VO) algorithm which leverages geometry-based methods and deep learning. Most existing VO/SLAM systems with superior performance…
Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video
Jia-Wang Bian, Zhichao Li, Naiyan Wang +4
Recent work has shown that CNN-based depth and ego-motion estimators can be learned using unlabelled monocular videos. However, the performance is limited by unidentified moving ob…
Semantic Edge Detection with Diverse Deep Supervision
Yun Liu, Ming-Ming Cheng, Deng-Ping Fan +3
Semantic edge detection (SED), which aims at jointly extracting edges as well as their category information, has far-reaching applications in domains such as semantic segmentation,…
Richer Convolutional Features for Edge Detection
Yun Liu, Ming-Ming Cheng, Xiaowei Hu +2
In this paper, we propose an accurate edge detector using richer convolutional features (RCF). Since objects in nature images have various scales and aspect ratios, the automatical…