activity
20092023
most citedOmni-frequency Channel-selection Representations for Unsupervised Anomaly Detection

235 citations · 785 across the 49 of their papers we have counts for

collaborators

49 papers

cs.CV2023★ 11 cited

Real3D-AD: A Dataset of Point Cloud Anomaly Detection

Jiaqi Liu, Guoyang Xie, Ruitao Chen +5

High-precision point cloud anomaly detection is the gold standard for identifying the defects of advancing machining and precision manufacturing. Despite some methodological advanc…

math.AP2023

Uniqueness of lump solutions of KP-I equation

Yong Liu, Jun-cheng Wei, Wen Yang

The KP-I equation has family of solutions which decay to zero at space infinity. One of these solutions is the classical lump solution. This is a traveling wave, and the KP-I equat…

cs.CV2023

Synchronize Feature Extracting and Matching: A Single Branch Framework for 3D Object Tracking

Teli Ma, Mengmeng Wang, Jimin Xiao +2

Siamese network has been a de facto benchmark framework for 3D LiDAR object tracking with a shared-parametric encoder extracting features from template and search region, respectiv…

cs.CV2023★ 2 cited

Boosting Few-shot Action Recognition with Graph-guided Hybrid Matching

Jiazheng Xing, Mengmeng Wang, Yudi Ruan +6

Class prototype construction and matching are core aspects of few-shot action recognition. Previous methods mainly focus on designing spatiotemporal relation modeling modules or co…

cs.CV2023

SSC-RS: Elevate LiDAR Semantic Scene Completion with Representation Separation and BEV Fusion

Jianbiao Mei, Yu Yang, Mengmeng Wang +3

Semantic scene completion (SSC) jointly predicts the semantics and geometry of the entire 3D scene, which plays an essential role in 3D scene understanding for autonomous driving s…

cs.CV2023

PANet: LiDAR Panoptic Segmentation with Sparse Instance Proposal and Aggregation

Jianbiao Mei, Yu Yang, Mengmeng Wang +3

Reliable LiDAR panoptic segmentation (LPS), including both semantic and instance segmentation, is vital for many robotic applications, such as autonomous driving. This work propose…