Search Results for author: Jie Nie

Found 8 papers, 1 papers with code

A Semantic-aware Attention and Visual Shielding Network for Cloth-changing Person Re-identification

no code implementations18 Jul 2022 Zan Gao, Hongwei Wei, Weili Guan, Jie Nie, Meng Wang, Shenyong Chen

In addition, a visual clothes shielding module (VCS) is also designed to extract a more robust feature representation for the cloth-changing task by covering the clothing regions and focusing the model on the visual semantic information unrelated to the clothes.

Cloth-Changing Person Re-Identification Semantic Segmentation

Scale-Semantic Joint Decoupling Network for Image-text Retrieval in Remote Sensing

no code implementations12 Dec 2022 Chengyu Zheng, Ning Song, Ruoyu Zhang, Lei Huang, Zhiqiang Wei, Jie Nie

To address these issues, we propose a novel Scale-Semantic Joint Decoupling Network (SSJDN) for remote sensing image-text retrieval.

Cross-Modal Retrieval Retrieval +1

Causal Disentanglement Hidden Markov Model for Fault Diagnosis

no code implementations6 Aug 2023 Rihao Chang, Yongtao Ma, Weizhi Nie, Jie Nie, An-An Liu

In modern industries, fault diagnosis has been widely applied with the goal of realizing predictive maintenance.

Disentanglement Time Series +1

LR-CNN: Lightweight Row-centric Convolutional Neural Network Training for Memory Reduction

no code implementations21 Jan 2024 Zhigang Wang, Hangyu Yang, Ning Wang, Chuanfei Xu, Jie Nie, Zhiqiang Wei, Yu Gu, Ge Yu

However, training its complex network is very space-consuming, since a lot of intermediate data are preserved across layers, especially when processing high-dimension inputs with a big batch size.

LoDisc: Learning Global-Local Discriminative Features for Self-Supervised Fine-Grained Visual Recognition

no code implementations6 Mar 2024 Jialu Shi, Zhiqiang Wei, Jie Nie, Lei Huang

In this paper, we present to incorporate the subtle local fine-grained feature learning into global self-supervised contrastive learning through a pure self-supervised global-local fine-grained contrastive learning framework.

Contrastive Learning Fine-Grained Visual Recognition +3

LNPT: Label-free Network Pruning and Training

no code implementations19 Mar 2024 Jinying Xiao, Ping Li, Zhe Tang, Jie Nie

Pruning before training enables the deployment of neural networks on smart devices.

Network Pruning

SEVEN: Pruning Transformer Model by Reserving Sentinels

1 code implementation19 Mar 2024 Jinying Xiao, Ping Li, Jie Nie, Zhe Tang

We utilize this design to dynamically assess the importance scores of weights. SEVEN is introduced by us, which particularly favors weights with consistently high sensitivity, i. e., weights with small gradient noise.

Image Classification Question Answering

Object-level Copy-Move Forgery Image Detection based on Inconsistency Mining

no code implementations31 Mar 2024 Jingyu Wang, Niantai Jing, Ziyao Liu, Jie Nie, Yuxin Qi, Chi-Hung Chi, Kwok-Yan Lam

Additionally, we extract inconsistent regions between coarse similar regions obtained through self-correlation calculations and regions composed of prototypes.

Object

Cannot find the paper you are looking for? You can Submit a new open access paper.