Search Results for author: Lefei Zhang

Found 30 papers, 16 papers with code

Deformable Mixer Transformer with Gating for Multi-Task Learning of Dense Prediction

1 code implementation10 Aug 2023 Yangyang Xu, Yibo Yang, Bernard Ghanem, Lefei Zhang, Du Bo, DaCheng Tao

In this work, we present a novel MTL model by combining both merits of deformable CNN and query-based Transformer with shared gating for multi-task learning of dense prediction.

Multi-Task Learning

Neural Collapse Terminus: A Unified Solution for Class Incremental Learning and Its Variants

2 code implementations3 Aug 2023 Yibo Yang, Haobo Yuan, Xiangtai Li, Jianlong Wu, Lefei Zhang, Zhouchen Lin, Philip Torr, DaCheng Tao, Bernard Ghanem

Beyond the normal case, long-tail class incremental learning and few-shot class incremental learning are also proposed to consider the data imbalance and data scarcity, respectively, which are common in real-world implementations and further exacerbate the well-known problem of catastrophic forgetting.

class-incremental learning Few-Shot Class-Incremental Learning +1

Bidirectional Looking with A Novel Double Exponential Moving Average to Adaptive and Non-adaptive Momentum Optimizers

1 code implementation2 Jul 2023 Yineng Chen, Zuchao Li, Lefei Zhang, Bo Du, Hai Zhao

SGD and Adam are two classical and effective optimizers on which researchers have proposed many variants, such as SGDM and RAdam.

Bidirectional Correlation-Driven Inter-Frame Interaction Transformer for Referring Video Object Segmentation

no code implementations2 Jul 2023 Meng Lan, Fu Rong, Zuchao Li, Wei Yu, Lefei Zhang

Moreover, a bidirectional vision-language interaction module is implemented before the multimodal Transformer to enhance the correlation between the visual and linguistic features, thus facilitating the language queries to decode more precise object information from visual features and ultimately improving the segmentation performance.

Referring Video Object Segmentation Representation Learning +2

ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration

1 code implementation23 Jun 2023 Jiaqi Ma, Tianheng Cheng, Guoli Wang, Qian Zhang, Xinggang Wang, Lefei Zhang

We then leverage degradation-aware visual prompts to establish a controllable and universal model for image restoration, called ProRes, which is applicable to an extensive range of image restoration tasks.

Deblurring Denoising +1

FSUIE: A Novel Fuzzy Span Mechanism for Universal Information Extraction

1 code implementation19 Jun 2023 Tianshuo Peng, Zuchao Li, Lefei Zhang, Bo Du, Hai Zhao

To address these deficiencies, we propose the Fuzzy Span Universal Information Extraction (FSUIE) framework.


Centroid-centered Modeling for Efficient Vision Transformer Pre-training

no code implementations8 Mar 2023 Xin Yan, Zuchao Li, Lefei Zhang, Bo Du, DaCheng Tao

Our proposed approach, \textbf{CCViT}, leverages k-means clustering to obtain centroids for image modeling without supervised training of tokenizer model.

Semantic Segmentation

DeMT: Deformable Mixer Transformer for Multi-Task Learning of Dense Prediction

2 code implementations9 Jan 2023 Yangyang Xu, Yibo Yang, Lefei Zhang

In this work, we present a novel MTL model by combining both merits of deformable CNN and query-based Transformer for multi-task learning of dense prediction.

Multi-Task Learning

Learning to Learn Better for Video Object Segmentation

1 code implementation5 Dec 2022 Meng Lan, Jing Zhang, Lefei Zhang, DaCheng Tao

Recently, the joint learning framework (JOINT) integrates matching based transductive reasoning and online inductive learning to achieve accurate and robust semi-supervised video object segmentation (SVOS).

Semantic Segmentation Semi-Supervised Video Object Segmentation +1

ELMformer: Efficient Raw Image Restoration with a Locally Multiplicative Transformer

no code implementations31 Aug 2022 Jiaqi Ma, Shengyuan Yan, Lefei Zhang, Guoli Wang, Qian Zhang

In order to get raw images of high quality for downstream Image Signal Process (ISP), in this paper we present an Efficient Locally Multiplicative Transformer called ELMformer for raw image restoration.

Deblurring Denoising +1

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

2 code implementations11 May 2022 Yawei Li, Kai Zhang, Radu Timofte, Luc van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wu1, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoğlu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gaoand Dengwen Zhouand Qian Ning, Jingzhu Tang, Han Huang, YuFei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Dengwen Zhou, Kun Zeng, Hanjiang Lin, Xinyu Chen, Jinsheng Fang

The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.

Image Super-Resolution

Siamese Network with Interactive Transformer for Video Object Segmentation

1 code implementation28 Dec 2021 Meng Lan, Jing Zhang, Fengxiang He, Lefei Zhang

Semi-supervised video object segmentation (VOS) refers to segmenting the target object in remaining frames given its annotation in the first frame, which has been actively studied in recent years.

Semantic Segmentation Semi-Supervised Video Object Segmentation +1

Monocular Road Planar Parallax Estimation

no code implementations22 Nov 2021 Haobo Yuan, Teng Chen, Wei Sui, Jiafeng Xie, Lefei Zhang, Yuan Li, Qian Zhang

It implies planar parallax and can be combined with the road plane serving as a reference to estimate the 3D structure by warping the consecutive frames.

3D Reconstruction Autonomous Driving

DSP: Dual Soft-Paste for Unsupervised Domain Adaptive Semantic Segmentation

1 code implementation20 Jul 2021 Li Gao, Jing Zhang, Lefei Zhang, DaCheng Tao

In addition, feature-level alignment is carried out by aligning the feature maps of the source and target images from student network using a weighted maximum mean discrepancy loss.

Semantic Segmentation Synthetic-to-Real Translation +1

Transportation Density Reduction Caused by City Lockdowns Across the World during the COVID-19 Epidemic: From the View of High-resolution Remote Sensing Imagery

no code implementations2 Mar 2021 Chen Wu, Sihan Zhu, Jiaqi Yang, Meiqi Hu, Bo Du, Liangpei Zhang, Lefei Zhang, Chengxi Han, Meng Lan

Considering that public transportation was mostly reduced or even forbidden, our results indicate that city lockdown policies are effective at limiting human transmission within cities.

LocalDrop: A Hybrid Regularization for Deep Neural Networks

no code implementations1 Mar 2021 Ziqing Lu, Chang Xu, Bo Du, Takashi Ishida, Lefei Zhang, Masashi Sugiyama

In neural networks, developing regularization algorithms to settle overfitting is one of the major study areas.

Recurrent Feature Reasoning for Image Inpainting

1 code implementation CVPR 2020 Jingyuan Li, Ning Wang, Lefei Zhang, Bo Du, DaCheng Tao

To capture information from distant places in the feature map for RFR, we further develop KCA and incorporate it in RFR.

Image Inpainting SSIM

Multi-scale Dynamic Graph Convolutional Network for Hyperspectral Image Classification

1 code implementation14 May 2019 Sheng Wan, Chen Gong, Ping Zhong, Bo Du, Lefei Zhang, Jian Yang

To alleviate this shortcoming, we consider employing the recently proposed Graph Convolutional Network (GCN) for hyperspectral image classification, as it can conduct the convolution on arbitrarily structured non-Euclidean data and is applicable to the irregular image regions represented by graph topological information.

Classification General Classification +1

Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images

no code implementations8 Apr 2019 Lefei Zhang, Qian Zhang, Bo Du, Xin Huang, Yuan Yan Tang, DaCheng Tao

In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial features into a single but high dimensional vector and then apply a certain dimension reduction technique directly on that concatenated vector before feed it into the subsequent classifier.

Dimensionality Reduction feature selection +2

Defect Detection from UAV Images based on Region-Based CNNs

no code implementations23 Nov 2018 Meng Lan, YiPeng Zhang, Lefei Zhang, Bo Du

In this work, we study the performance of the region-based CNN for the electrical equipment defect detection by using the UAV images.

Defect Detection object-detection +1

TLR: Transfer Latent Representation for Unsupervised Domain Adaptation

no code implementations19 Aug 2018 Pan Xiao, Bo Du, Jia Wu, Lefei Zhang, Ruimin Hu, Xuelong. Li

Many classic methods solve the domain adaptation problem by establishing a common latent space, which may cause the loss of many important properties across both domains.

Unsupervised Domain Adaptation

Unsupervised Domain Adaptive Re-Identification: Theory and Practice

3 code implementations30 Jul 2018 Liangchen Song, Cheng Wang, Lefei Zhang, Bo Du, Qian Zhang, Chang Huang, Xinggang Wang

We study the problem of unsupervised domain adaptive re-identification (re-ID) which is an active topic in computer vision but lacks a theoretical foundation.

General Classification Unsupervised Domain Adaptation

Tensor Representation and Manifold Learning Methods for Remote Sensing Images

no code implementations13 Jan 2014 Lefei Zhang

One of the main purposes of earth observation is to extract interested information and knowledge from remote sensing (RS) images with high efficiency and accuracy.

Sparse Learning Transfer Learning

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