Search Results for author: Xing Fu

Found 9 papers, 0 papers with code

Clean-image Backdoor Attacks

no code implementations22 Mar 2024 Dazhong Rong, Guoyao Yu, Shuheng Shen, Xinyi Fu, Peng Qian, Jianhai Chen, Qinming He, Xing Fu, Weiqiang Wang

To gather a significant quantity of annotated training data for high-performance image classification models, numerous companies opt to enlist third-party providers to label their unlabeled data.

Fairness Image Classification

Self-supervision meets kernel graph neural models: From architecture to augmentations

no code implementations17 Oct 2023 Jiawang Dan, Ruofan Wu, Yunpeng Liu, Baokun Wang, Changhua Meng, Tengfei Liu, Tianyi Zhang, Ningtao Wang, Xing Fu, Qi Li, Weiqiang Wang

Recently, the idea of designing neural models on graphs using the theory of graph kernels has emerged as a more transparent as well as sometimes more expressive alternative to MPNNs known as kernel graph neural networks (KGNNs).

Data Augmentation Graph Classification +2

Non-Line-of-Sight Imaging With Signal Superresolution Network

no code implementations CVPR 2023 Jianyu Wang, Xintong Liu, Leping Xiao, Zuoqiang Shi, Lingyun Qiu, Xing Fu

This paper proposes a general learning-based pipeline for increasing imaging quality with only a few scanning points.

Differentially Private Learning with Per-Sample Adaptive Clipping

no code implementations1 Dec 2022 Tianyu Xia, Shuheng Shen, Su Yao, Xinyi Fu, Ke Xu, Xiaolong Xu, Xing Fu

As one way to implement privacy-preserving AI, differentially private learning is a framework that enables AI models to use differential privacy (DP).

Privacy Preserving

Few-shot Non-line-of-sight Imaging with Signal-surface Collaborative Regularization

no code implementations CVPR 2023 Xintong Liu, Jianyu Wang, Leping Xiao, Xing Fu, Lingyun Qiu, Zuoqiang Shi

In this work, we propose a signal-surface collaborative regularization (SSCR) framework that provides noise-robust reconstructions with a minimal number of measurements.

Autonomous Driving Bayesian Inference

Non-line-of-sight imaging with arbitrary illumination and detection pattern

no code implementations1 Nov 2022 Xintong Liu, Jianyu Wang, Leping Xiao, Zuoqiang Shi, Xing Fu, Lingyun Qiu

Non-line-of-sight (NLOS) imaging aims at reconstructing targets obscured from the direct line of sight.

Autonomous Driving

SHORING: Design Provable Conditional High-Order Interaction Network via Symbolic Testing

no code implementations3 Jul 2021 Hui Li, Xing Fu, Ruofan Wu, Jinyu Xu, Kai Xiao, xiaofu Chang, Weiqiang Wang, Shuai Chen, Leilei Shi, Tao Xiong, Yuan Qi

Deep learning provides a promising way to extract effective representations from raw data in an end-to-end fashion and has proven its effectiveness in various domains such as computer vision, natural language processing, etc.

Management Product Recommendation +1

Coherent ray-wave structured light based on (helical) Ince-Gaussian modes

no code implementations4 Feb 2021 Zhaoyang Wang, Yijie Shen, Qiang Liu, Xing Fu

The topological evolution of classic eigenmodes including Hermite-Laguerre-Gaussian and (helical) InceGaussian modes is exploited to construct coherent state modes, which unifies the representations of travelingwave (TW) and standing-wave (SW) ray-wave structured light for the first time and realizes the TW-SW unified ray-wave geometric beam with topology of raytrajectories splitting effect, breaking the boundary of TW and SW structured light.

Optics

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