Search Results for author: Zhiyu Zhu

Found 21 papers, 15 papers with code

Benchmarking Transferable Adversarial Attacks

1 code implementation1 Feb 2024 Zhibo Jin, Jiayu Zhang, Zhiyu Zhu, Huaming Chen

The robustness of deep learning models against adversarial attacks remains a pivotal concern.

Adversarial Attack Benchmarking +2

GE-AdvGAN: Improving the transferability of adversarial samples by gradient editing-based adversarial generative model

1 code implementation11 Jan 2024 Zhiyu Zhu, Huaming Chen, Xinyi Wang, Jiayu Zhang, Zhibo Jin, Kim-Kwang Raymond Choo, Jun Shen, Dong Yuan

With the functional and characteristic similarity analysis, we introduce a novel gradient editing (GE) mechanism and verify its feasibility in generating transferable samples on various models.

Adversarial Attack

Segment Any Events via Weighted Adaptation of Pivotal Tokens

1 code implementation24 Dec 2023 Zhiwen Chen, Zhiyu Zhu, Yifan Zhang, Junhui Hou, Guangming Shi, Jinjian Wu

One pivotal issue at the heart of this endeavor is the precise alignment and calibration of embeddings derived from event-centric data such that they harmoniously coincide with those originating from RGB imagery.

Event-based Object Segmentation

MFABA: A More Faithful and Accelerated Boundary-based Attribution Method for Deep Neural Networks

1 code implementation21 Dec 2023 Zhiyu Zhu, Huaming Chen, Jiayu Zhang, Xinyi Wang, Zhibo Jin, Minhui Xue, Dongxiao Zhu, Kim-Kwang Raymond Choo

To better understand the output of deep neural networks (DNN), attribution based methods have been an important approach for model interpretability, which assign a score for each input dimension to indicate its importance towards the model outcome.

Global Structure-Aware Diffusion Process for Low-Light Image Enhancement

1 code implementation NeurIPS 2023 Jinhui Hou, Zhiyu Zhu, Junhui Hou, Hui Liu, Huanqiang Zeng, Hui Yuan

To harness the capabilities of diffusion models, we delve into this intricate process and advocate for the regularization of its inherent ODE-trajectory.

Low-Light Image Enhancement

DANAA: Towards transferable attacks with double adversarial neuron attribution

1 code implementation16 Oct 2023 Zhibo Jin, Zhiyu Zhu, Xinyi Wang, Jiayu Zhang, Jun Shen, Huaming Chen

While deep neural networks have excellent results in many fields, they are susceptible to interference from attacking samples resulting in erroneous judgments.

Feature Importance

Spatial-Temporal Enhanced Transformer Towards Multi-Frame 3D Object Detection

1 code implementation1 Jul 2023 Yifan Zhang, Zhiyu Zhu, Junhui Hou, Dapeng Wu

Specifically, to model the inter-object spatial interaction and complex temporal dependencies, we introduce the spatial-temporal graph attention network, which represents queries as nodes in a graph and enables effective modeling of object interactions within a social context.

3D Object Detection Graph Attention +2

Deep Diversity-Enhanced Feature Representation of Hyperspectral Images

1 code implementation15 Jan 2023 Jinhui Hou, Zhiyu Zhu, Junhui Hou, Hui Liu, Huanqiang Zeng, Deyu Meng

In this paper, we study the problem of efficiently and effectively embedding the high-dimensional spatio-spectral information of hyperspectral (HS) images, guided by feature diversity.

Denoising Super-Resolution

GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation

1 code implementation6 Jul 2022 Yifan Zhang, Qijian Zhang, Zhiyu Zhu, Junhui Hou, Yixuan Yuan

The label uncertainty generated by GLENet is a plug-and-play module and can be conveniently integrated into existing deep 3D detectors to build probabilistic detectors and supervise the learning of the localization uncertainty.

3D Object Detection

Deep Posterior Distribution-based Embedding for Hyperspectral Image Super-resolution

1 code implementation30 May 2022 Jinhui Hou, Zhiyu Zhu, Junhui Hou, Huanqiang Zeng, Jinjian Wu, Jiantao Zhou

Then, we incorporate the proposed feature embedding scheme into a source-consistent super-resolution framework that is physically-interpretable, producing lightweight PDE-Net, in which high-resolution (HR) HS images are iteratively refined from the residuals between input low-resolution (LR) HS images and pseudo-LR-HS images degenerated from reconstructed HR-HS images via probability-inspired HS embedding.

Hyperspectral Image Super-Resolution Image Super-Resolution

Positioning Using Visible Light Communications: A Perspective Arcs Approach

no code implementations18 Apr 2022 Zhiyu Zhu, Caili Guo, Rongzhen Bao, Mingzhe Chen, Walid Saad, Yang Yang

In this paper, the arc feature of the circular luminaire and the coordinate information obtained via visible light communication (VLC) are jointly used for VLC-enabled indoor positioning, and a novel perspective arcs approach is proposed.

Semantic-embedded Unsupervised Spectral Reconstruction from Single RGB Images in the Wild

1 code implementation ICCV 2021 Zhiyu Zhu, Hui Liu, Junhui Hou, Huanqiang Zeng, Qingfu Zhang

Specifically, on the basis of the intrinsic imaging degradation model of RGB images from HS images, we progressively spread the differences between input RGB images and re-projected RGB images from recovered HS images via effective unsupervised camera spectral response function estimation.

Image Reconstruction Spectral Reconstruction +1

Deep Amended Gradient Descent for Efficient Spectral Reconstruction from Single RGB Images

1 code implementation12 Aug 2021 Zhiyu Zhu, Hui Liu, Junhui Hou, Sen Jia, Qingfu Zhang

Then, we design a lightweight neural network with a multi-stage architecture to mimic the formed amended gradient descent process, in which efficient convolution and novel spectral zero-mean normalization are proposed to effectively extract spatial-spectral features for regressing an initialization, a basic gradient, and an incremental gradient.

Spectral Reconstruction

CorrNet3D: Unsupervised End-to-end Learning of Dense Correspondence for 3D Point Clouds

1 code implementation CVPR 2021 Yiming Zeng, Yue Qian, Zhiyu Zhu, Junhui Hou, Hui Yuan, Ying He

The symmetric deformer, with an additional regularized loss, transforms the two permuted point clouds to each other to drive the unsupervised learning of the correspondence.

Ranked #6 on 3D Dense Shape Correspondence on SHREC'19 (using extra training data)

3D Dense Shape Correspondence

Deep Selective Combinatorial Embedding and Consistency Regularization for Light Field Super-resolution

no code implementations26 Sep 2020 Jing Jin, Junhui Hou, Zhiyu Zhu, Jie Chen, Sam Kwong

To preserve the parallax structure among the reconstructed SAIs, we subsequently append a consistency regularization network trained over a structure-aware loss function to refine the parallax relationships over the coarse estimation.

Disparity Estimation Super-Resolution

Hyperspectral Image Super-resolution via Deep Progressive Zero-centric Residual Learning

1 code implementation18 Jun 2020 Zhiyu Zhu, Junhui Hou, Jie Chen, Huanqiang Zeng, Jiantao Zhou

Specifically, PZRes-Net learns a high resolution and \textit{zero-centric} residual image, which contains high-frequency spatial details of the scene across all spectral bands, from both inputs in a progressive fashion along the spectral dimension.

Hyperspectral Image Super-Resolution Hyperspectral Unmixing +1

Power Efficient LED Placement Algorithm for Indoor Visible Light Communication

no code implementations17 Jun 2020 Yang Yang, Zhiyu Zhu, Caili Guo, Chunyan Feng

Due to the interactions among LEDs and the illumination uniformity constraint, the formulated problem is complex and non-convex.

When Residual Learning Meets Dense Aggregation: Rethinking the Aggregation of Deep Neural Networks

no code implementations19 Apr 2020 Zhiyu Zhu, Zhen-Peng Bian, Junhui Hou, Yi Wang, Lap-Pui Chau

However, the existing networks usually suffer from either redundancy of convolutional layers or insufficient utilization of parameters.

Neural Architecture Search

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