181 citations · 244 across the 16 of their papers we have counts for
16 papers
Curvature-Aware Zeroth-Order Optimization for Memory-Efficient Test-Time Adaptation
Junming Zhang, Shuyu Yin, Peilin Liu +2
Test-time adaptation (TTA) aims to enhance the cross-domain performance of pre-trained models by adapting to unlabeled test data. While most existing TTA methods rely on backpropag…
SSMG-Nav: Enhancing Lifelong Object Navigation with Semantic Skeleton Memory Graph
Haochen Niu, Lantao Zhang, Xingwu Ji +3
Navigating to out-of-sight targets from human instructions in unfamiliar environments is a core capability for service robots. Despite substantial progress, most approaches underut…
A High-Throughput Spiking Neural Network Processor Enabling Synaptic Delay Emulation
Faquan Chen, Qingyang Tian, Ziren Wu +3
Synaptic delay has attracted significant attention in neural network dynamics for integrating and processing complex spatiotemporal information. This paper introduces a high-throug…
An Online Adaptation Method for Robust Depth Estimation and Visual Odometry in the Open World
Xingwu Ji, Haochen Niu, Dexin Duan +3
Recently, learning-based robotic navigation systems have gained extensive research attention and made significant progress. However, the diversity of open-world scenarios poses a m…
A Skeleton-Based Topological Planner for Exploration in Complex Unknown Environments
Haochen Niu, Xingwu Ji, Lantao Zhang +3
The capability of autonomous exploration in complex, unknown environments is important in many robotic applications. While recent research on autonomous exploration have achieved m…
Loop Closure Detection Based on Object-level Spatial Layout and Semantic Consistency
Xingwu Ji, Peilin Liu, Haochen Niu +3
Visual simultaneous localization and mapping (SLAM) systems face challenges in detecting loop closure under the circumstance of large viewpoint changes. In this paper, we present a…
A life-long SLAM approach using adaptable local maps based on rasterized LIDAR images
Waqas Ali, Peilin Liu, Rendong Ying +1
Most real-time autonomous robot applications require a robot to traverse through a dynamic space for a long time. In some cases, a robot needs to work in the same environment. Such…
On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training Framework
Zeyu Yan, Fei Wen, Rendong Ying +2
Lossy compression algorithms are typically designed to achieve the lowest possible distortion at a given bit rate. However, recent studies show that pursuing high perceptual qualit…
6-DOF Feature based LIDAR SLAM using ORB Features from Rasterized Images of 3D LIDAR Point Cloud
Waqas Ali, Peilin Liu, Rendong Ying +1
An accurate and computationally efficient SLAM algorithm is vital for modern autonomous vehicles. To make a lightweight the algorithm, most SLAM systems rely on feature detection f…
A Simple Local Minimal Intensity Prior and An Improved Algorithm for Blind Image Deblurring
Fei Wen, Rendong Ying, Yipeng Liu +2
Blind image deblurring is a long standing challenging problem in image processing and low-level vision. Recently, sophisticated priors such as dark channel prior, extreme channel p…
Matrix Completion via Nonconvex Regularization: Convergence of the Proximal Gradient Algorithm
Fei Wen, Rendong Ying, Peilin Liu +1
Matrix completion has attracted much interest in the past decade in machine learning and computer vision. For low-rank promotion in matrix completion, the nuclear norm penalty is c…
3DTI-Net: Learn Inner Transform Invariant 3D Geometry Features using Dynamic GCN
Guanghua Pan, Jun Wang, Rendong Ying +1
Deep learning on point clouds has made a lot of progress recently. Many point cloud dedicated deep learning frameworks, such as PointNet and PointNet++, have shown advantages in ac…
Efficient Outlier Removal in Large Scale Global Structure-from-Motion
Fei Wen, Danping Zou, Rendong Ying +1
This work addresses the outlier removal problem in large-scale global structure-from-motion. In such applications, global outlier removal is very useful to mitigate the deteriorati…
Efficient Minimization Algorithms for Compressive Sensing Based on Proximity Operator
Fei Wen, Yuan Yang, Peilin Liu +2
This paper considers solving the unconstrained -norm () regularized least squares (-LS) problem for recovering sparse signals in compressive sensing. We…
Distributed Compressed Sensing off the Grid
Zhenqi Lu, Rendong Ying, Sumxin Jiang +2
This letter investigates the joint recovery of a frequency-sparse signal ensemble sharing a common frequency-sparse component from the collection of their compressed measurements.…
Spectral Compressive Sensing with Model Selection
Zhenqi Lu, Rendong Ying, Sumxin Jiang +3
The performance of existing approaches to the recovery of frequency-sparse signals from compressed measurements is limited by the coherence of required sparsity dictionaries and th…