Search Results for author: Wenxuan Wu

Found 11 papers, 7 papers with code

PointPWC-Net: Cost Volume on Point Clouds for (Self-)Supervised Scene Flow Estimation

1 code implementation ECCV 2020 Wenxuan Wu, Zhi Yuan Wang, Zhuwen Li, Wei Liu, Li Fuxin

We propose a novel end-to-end deep scene flow model, called PointPWC-Net, that directly processes 3D point cloud scenes with large motions in a coarse-to-fine fashion.

Self-supervised Scene Flow Estimation

MetaSeg: Content-Aware Meta-Net for Omni-Supervised Semantic Segmentation

no code implementations22 Jan 2024 Shenwang Jiang, Jianan Li, Ying Wang, Wenxuan Wu, Jizhou Zhang, Bo Huang, Tingfa Xu

Noisy labels, inevitably existing in pseudo segmentation labels generated from weak object-level annotations, severely hampers model optimization for semantic segmentation.

Meta-Learning Model Optimization +2

Kick Bad Guys Out! Zero-Knowledge-Proof-Based Anomaly Detection in Federated Learning

no code implementations6 Oct 2023 Shanshan Han, Wenxuan Wu, Baturalp Buyukates, Weizhao Jin, Qifan Zhang, Yuhang Yao, Salman Avestimehr, Chaoyang He

Federated Learning (FL) systems are vulnerable to adversarial attacks, where malicious clients submit poisoned models to prevent the global model from converging or plant backdoors to induce the global model to misclassify some samples.

Anomaly Detection Federated Learning

PointConvFormer: Revenge of the Point-based Convolution

no code implementations CVPR 2023 Wenxuan Wu, Li Fuxin, Qi Shan

Hence, we preserved the invariances from point convolution, whereas attention helps to select relevant points in the neighborhood for convolution.

Scene Flow Estimation Semantic Segmentation

The Devils in the Point Clouds: Studying the Robustness of Point Cloud Convolutions

no code implementations19 Jan 2021 Xingyi Li, Wenxuan Wu, Xiaoli Z. Fern, Li Fuxin

This paper investigates different variants of PointConv, a convolution network on point clouds, to examine their robustness to input scale and rotation changes.

Semantic Segmentation

UVMBench: A Comprehensive Benchmark Suite for Researching Unified Virtual Memory in GPUs

1 code implementation20 Jul 2020 Yongbin Gu, Wenxuan Wu, Yunfan Li, Lizhong Chen

The recent introduction of Unified Virtual Memory (UVM) in GPUs offers a new programming model that allows GPUs and CPUs to share the same virtual memory space, shifts the complex memory management from programmers to GPU driver/ hardware, and enables kernel execution even when memory is oversubscribed.

Hardware Architecture

Visualizing Point Cloud Classifiers by Curvature Smoothing

1 code implementation23 Nov 2019 Chen Ziwen, Wenxuan Wu, Zhongang Qi, Li Fuxin

In this paper, we propose a novel approach to visualize features important to the point cloud classifiers.

Data Augmentation General Classification

PointConv: Deep Convolutional Networks on 3D Point Clouds

9 code implementations CVPR 2019 Wenxuan Wu, Zhongang Qi, Li Fuxin

Besides, our experiments converting CIFAR-10 into a point cloud showed that networks built on PointConv can match the performance of convolutional networks in 2D images of a similar structure.

3D Part Segmentation 3D Point Cloud Classification +1

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