Search Results for author: Xue Yang

Found 55 papers, 35 papers with code

STAR: A First-Ever Dataset and A Large-Scale Benchmark for Scene Graph Generation in Large-Size Satellite Imagery

3 code implementations13 Jun 2024 Yansheng Li, LinLin Wang, Tingzhu Wang, Xue Yang, Junwei Luo, Qi Wang, Youming Deng, Wenbin Wang, Xian Sun, Haifeng Li, Bo Dang, Yongjun Zhang, Yi Yu, Junchi Yan

This paper constructs a large-scale dataset for SGG in large-size VHR SAI with image sizes ranging from 512 x 768 to 27, 860 x 31, 096 pixels, named STAR (Scene graph generaTion in lArge-size satellite imageRy), encompassing over 210K objects and over 400K triplets.

Graph Generation Object +3

Towards Vision-Language Geo-Foundation Model: A Survey

1 code implementation13 Jun 2024 Yue Zhou, Litong Feng, Yiping Ke, Xue Jiang, Junchi Yan, Xue Yang, Wayne Zhang

Vision-Language Foundation Models (VLFMs) have made remarkable progress on various multimodal tasks, such as image captioning, image-text retrieval, visual question answering, and visual grounding.

Earth Observation Image Captioning +5

UCDNet: Multi-UAV Collaborative 3D Object Detection Network by Reliable Feature Mapping

no code implementations7 Jun 2024 Pengju Tian, Peirui Cheng, Yuchao Wang, Zhechao Wang, Zhirui Wang, Menglong Yan, Xue Yang, Xian Sun

Multi-UAV collaborative 3D object detection can perceive and comprehend complex environments by integrating complementary information, with applications encompassing traffic monitoring, delivery services and agricultural management.

3D Object Detection Management +2

Parameter-Inverted Image Pyramid Networks

1 code implementation6 Jun 2024 Xizhou Zhu, Xue Yang, Zhaokai Wang, Hao Li, Wenhan Dou, Junqi Ge, Lewei Lu, Yu Qiao, Jifeng Dai

Our core idea is to use models with different parameter sizes to process different resolution levels of the image pyramid, thereby balancing computational efficiency and performance.

Computational Efficiency Image Classification +2

FLoRA: Low-Rank Core Space for N-dimension

1 code implementation23 May 2024 Chongjie Si, Xuehui Wang, Xue Yang, Zhengqin Xu, Qingyun Li, Jifeng Dai, Yu Qiao, Xiaokang Yang, Wei Shen

To tackle the diversity of dimensional spaces across different foundation models and provide a more precise representation of the changes within these spaces, this paper introduces a generalized parameter-efficient fine-tuning framework, FLoRA, designed for various dimensional parameter space.

Tensor Decomposition

Target Speaker Extraction by Directly Exploiting Contextual Information in the Time-Frequency Domain

no code implementations27 Feb 2024 Xue Yang, Changchun Bao, Jing Zhou, Xianhong Chen

These weighting matrices reflect the similarity among different frames of the T-F representations and are further employed to obtain the consistent T-F representations of the enrollment.

Target Speaker Extraction

Auto MC-Reward: Automated Dense Reward Design with Large Language Models for Minecraft

no code implementations CVPR 2024 Hao Li, Xue Yang, Zhaokai Wang, Xizhou Zhu, Jie zhou, Yu Qiao, Xiaogang Wang, Hongsheng Li, Lewei Lu, Jifeng Dai

Many reinforcement learning environments (e. g., Minecraft) provide only sparse rewards that indicate task completion or failure with binary values.

reinforcement-learning

ADT: Agent-based Dynamic Thresholding for Anomaly Detection

no code implementations3 Dec 2023 Xue Yang, Enda Howley, Micheal Schukat

In this paper, we model thresholding in anomaly detection as a Markov Decision Process and propose an agent-based dynamic thresholding (ADT) framework based on a deep Q-network.

Anomaly Detection

P2RBox: Point Prompt Oriented Object Detection with SAM

no code implementations22 Nov 2023 Guangming Cao, Xuehui Yu, Wenwen Yu, Xumeng Han, Xue Yang, Guorong Li, Jianbin Jiao, Zhenjun Han

In this study, we introduce P2RBox, which employs point prompt to generate rotated box (RBox) annotation for oriented object detection.

Object object-detection +2

Toward Open Vocabulary Aerial Object Detection with CLIP-Activated Student-Teacher Learning

no code implementations20 Nov 2023 Yan Li, Weiwei Guo, Xue Yang, Ning Liao, Dunyun He, Jiaqi Zhou, Wenxian Yu

In this paper, we aim to develop open-vocabulary object detection (OVD) technique in aerial images that scales up object vocabulary size beyond training data.

Object object-detection +3

An Efficient Virtual Data Generation Method for Reducing Communication in Federated Learning

no code implementations21 Jun 2023 Cheng Yang, Xue Yang, Dongxian Wu, Xiaohu Tang

Then the server aggregates all the proxy datasets to form a central dummy dataset, which is used to finetune aggregated global model.

Federated Learning

An Efficient and Multi-private Key Secure Aggregation for Federated Learning

no code implementations15 Jun 2023 Xue Yang, Zifeng Liu, Xiaohu Tang, Rongxing Lu, Bo Liu

With the emergence of privacy leaks in federated learning, secure aggregation protocols that mainly adopt either homomorphic encryption or threshold secret sharing have been widely developed for federated learning to protect the privacy of the local training data of each client.

Federated Learning

InternGPT: Solving Vision-Centric Tasks by Interacting with ChatGPT Beyond Language

2 code implementations9 May 2023 Zhaoyang Liu, Yinan He, Wenhai Wang, Weiyun Wang, Yi Wang, Shoufa Chen, Qinglong Zhang, Zeqiang Lai, Yang Yang, Qingyun Li, Jiashuo Yu, Kunchang Li, Zhe Chen, Xue Yang, Xizhou Zhu, Yali Wang, LiMin Wang, Ping Luo, Jifeng Dai, Yu Qiao

Different from existing interactive systems that rely on pure language, by incorporating pointing instructions, the proposed iGPT significantly improves the efficiency of communication between users and chatbots, as well as the accuracy of chatbots in vision-centric tasks, especially in complicated visual scenarios where the number of objects is greater than 2.

Language Modelling

ARS-DETR: Aspect Ratio-Sensitive Detection Transformer for Aerial Oriented Object Detection

1 code implementation9 Mar 2023 Ying Zeng, Yushi Chen, Xue Yang, Qingyun Li, Junchi Yan

Existing oriented object detection methods commonly use metric AP$_{50}$ to measure the performance of the model.

Object object-detection +2

PatchDCT: Patch Refinement for High Quality Instance Segmentation

1 code implementation6 Feb 2023 Qinrou Wen, Jirui Yang, Xue Yang, Kewei Liang

To further refine masks obtained by compressed vectors, we propose for the first time a compressed vector based multi-stage refinement framework.

Instance Segmentation Semantic Segmentation +1

H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detection

3 code implementations13 Oct 2022 Xue Yang, Gefan Zhang, Wentong Li, Xuehui Wang, Yue Zhou, Junchi Yan

Oriented object detection emerges in many applications from aerial images to autonomous driving, while many existing detection benchmarks are annotated with horizontal bounding box only which is also less costive than fine-grained rotated box, leading to a gap between the readily available training corpus and the rising demand for oriented object detection.

Autonomous Driving Box-supervised Instance Segmentation +6

Detecting Rotated Objects as Gaussian Distributions and Its 3-D Generalization

1 code implementation22 Sep 2022 Xue Yang, Gefan Zhang, Xiaojiang Yang, Yue Zhou, Wentao Wang, Jin Tang, Tao He, Junchi Yan

Existing detection methods commonly use a parameterized bounding box (BBox) to model and detect (horizontal) objects and an additional rotation angle parameter is used for rotated objects.

regression

Black-box Dataset Ownership Verification via Backdoor Watermarking

1 code implementation4 Aug 2022 Yiming Li, Mingyan Zhu, Xue Yang, Yong Jiang, Tao Wei, Shu-Tao Xia

The rapid development of DNNs has benefited from the existence of some high-quality datasets ($e. g.$, ImageNet), which allow researchers and developers to easily verify the performance of their methods.

G-Rep: Gaussian Representation for Arbitrary-Oriented Object Detection

1 code implementation24 May 2022 Liping Hou, Ke Lu, Xue Yang, Yuqiu Li, Jian Xue

To go further, in this paper, we propose a unified Gaussian representation called G-Rep to construct Gaussian distributions for OBB, QBB, and PointSet, which achieves a unified solution to various representations and problems.

Object object-detection +3

MMRotate: A Rotated Object Detection Benchmark using PyTorch

1 code implementation28 Apr 2022 Yue Zhou, Xue Yang, Gefan Zhang, Jiabao Wang, Yanyi Liu, Liping Hou, Xue Jiang, Xingzhao Liu, Junchi Yan, Chengqi Lyu, Wenwei Zhang, Kai Chen

We present an open-source toolbox, named MMRotate, which provides a coherent algorithm framework of training, inferring, and evaluation for the popular rotated object detection algorithm based on deep learning.

Object object-detection +1

Embedding Recurrent Layers with Dual-Path Strategy in a Variant of Convolutional Network for Speaker-Independent Speech Separation

no code implementations25 Mar 2022 Xue Yang, Changchun Bao

Various network architectures, from traditional convolutional neural network (CNN) and recurrent neural network (RNN) to advanced transformer, have been designed sophistically to improve separation performance.

Computational Efficiency Speech Separation

Self-supervised Implicit Glyph Attention for Text Recognition

1 code implementation CVPR 2023 Tongkun Guan, Chaochen Gu, Jingzheng Tu, Xue Yang, Qi Feng, Yudi Zhao, Xiaokang Yang, Wei Shen

Supervised attention can alleviate the above issue, but it is character category-specific, which requires extra laborious character-level bounding box annotations and would be memory-intensive when handling languages with larger character categories.

Scene Text Recognition Text Segmentation

The KFIoU Loss for Rotated Object Detection

3 code implementations29 Jan 2022 Xue Yang, Yue Zhou, Gefan Zhang, Jirui Yang, Wentao Wang, Junchi Yan, Xiaopeng Zhang, Qi Tian

This is in contrast to recent Gaussian modeling based rotation detectors e. g. GWD loss and KLD loss that involve a human-specified distribution distance metric which require additional hyperparameter tuning that vary across datasets and detectors.

Object object-detection +1

Dual-Path Image Inpainting With Auxiliary GAN Inversion

no code implementations CVPR 2022 Wentao Wang, Li Niu, Jianfu Zhang, Xue Yang, Liqing Zhang

Different from feed-forward methods, they seek for a closest latent code to the corrupted image and feed it to a pretrained generator.

Image Inpainting

AlphaRotate: A Rotation Detection Benchmark using TensorFlow

1 code implementation12 Nov 2021 Xue Yang, Yue Zhou, Junchi Yan

AlphaRotate is an open-source Tensorflow benchmark for performing scalable rotation detection on various datasets.

RSDet++: Point-based Modulated Loss for More Accurate Rotated Object Detection

1 code implementation24 Sep 2021 Wen Qian, Xue Yang, Silong Peng, Junchi Yan, Xiujuan Zhang

We classify the discontinuity of loss in both five-param and eight-param rotated object detection methods as rotation sensitivity error (RSE) which will result in performance degeneration.

Object object-detection +1

An adaptive Origin-Destination flows cluster-detecting method to identify urban mobility trends

no code implementations10 Jun 2021 Mengyuan Fang, Luliang Tang, Zihan Kan, Xue Yang, Tao Pei, Qingquan Li, Chaokui Li

As an important spatial analysis approach, the clustering methods of point events have been extended to OD flows to identify the dominant trends and spatial structures of urban mobility.

Clustering

Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergence

2 code implementations NeurIPS 2021 Xue Yang, Xiaojiang Yang, Jirui Yang, Qi Ming, Wentao Wang, Qi Tian, Junchi Yan

Taking the perspective that horizontal detection is a special case for rotated object detection, in this paper, we are motivated to change the design of rotation regression loss from induction paradigm to deduction methodology, in terms of the relation between rotation and horizontal detection.

Ranked #15 on Object Detection In Aerial Images on DOTA (using extra training data)

object-detection Object Detection In Aerial Images +1

Optimization for Arbitrary-Oriented Object Detection via Representation Invariance Loss

1 code implementation22 Mar 2021 Qi Ming, Lingjuan Miao, Zhiqiang Zhou, Xue Yang, Yunpeng Dong

In this paper, we propose a Representation Invariance Loss (RIL) to optimize the bounding box regression for the rotating objects.

Ranked #28 on Object Detection In Aerial Images on DOTA (using extra training data)

Object object-detection +3

Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss

2 code implementations28 Jan 2021 Xue Yang, Junchi Yan, Qi Ming, Wentao Wang, Xiaopeng Zhang, Qi Tian

Boundary discontinuity and its inconsistency to the final detection metric have been the bottleneck for rotating detection regression loss design.

Ranked #17 on Object Detection In Aerial Images on DOTA (using extra training data)

object-detection Object Detection In Aerial Images +2

Parallel Multi-Resolution Fusion Network for Image Inpainting

no code implementations ICCV 2021 Wentao Wang, Jianfu Zhang, Li Niu, Haoyu Ling, Xue Yang, Liqing Zhang

Conventional deep image inpainting methods are based on auto-encoder architecture, in which the spatial details of images will be lost in the down-sampling process, leading to the degradation of generated results.

Image Inpainting

Dense Label Encoding for Boundary Discontinuity Free Rotation Detection

3 code implementations CVPR 2021 Xue Yang, Liping Hou, Yue Zhou, Wentao Wang, Junchi Yan

Rotation detection serves as a fundamental building block in many visual applications involving aerial image, scene text, and face etc.

Ranked #30 on Object Detection In Aerial Images on DOTA (using extra training data)

Classification General Classification +2

Rectified Decision Trees: Exploring the Landscape of Interpretable and Effective Machine Learning

no code implementations21 Aug 2020 Yiming Li, Jiawang Bai, Jiawei Li, Xue Yang, Yong Jiang, Shu-Tao Xia

Interpretability and effectiveness are two essential and indispensable requirements for adopting machine learning methods in reality.

BIG-bench Machine Learning Knowledge Distillation

On the Arbitrary-Oriented Object Detection: Classification based Approaches Revisited

4 code implementations ECCV 2020 Xue Yang, Junchi Yan

For the resulting circularly distributed angle classification problem, we first devise a Circular Smooth Label technique to handle the periodicity of angle and increase the error tolerance to adjacent angles.

Ranked #38 on Object Detection In Aerial Images on DOTA (using extra training data)

Classification General Classification +4

An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning

1 code implementation23 Feb 2020 Xue Yang, Yan Feng, Weijun Fang, Jun Shao, Xiaohu Tang, Shu-Tao Xia, Rongxing Lu

However, the strong defence ability and high learning accuracy of these schemes cannot be ensured at the same time, which will impede the wide application of FL in practice (especially for medical or financial institutions that require both high accuracy and strong privacy guarantee).

Federated Learning

Learning Modulated Loss for Rotated Object Detection

2 code implementations19 Nov 2019 Wen Qian, Xue Yang, Silong Peng, Yue Guo, Junchi Yan

Popular rotated detection methods usually use five parameters (coordinates of the central point, width, height, and rotation angle) to describe the rotated bounding box and l1-loss as the loss function.

Ranked #44 on Object Detection In Aerial Images on DOTA (using extra training data)

Object object-detection +2

Building Change Detection for Remote Sensing Images Using a Dual Task Constrained Deep Siamese Convolutional Network Model

no code implementations17 Sep 2019 Yi Liu, Chao Pang, Zongqian Zhan, Xiaomeng Zhang, Xue Yang

In recent years, building change detection methods have made great progress by introducing deep learning, but they still suffer from the problem of the extracted features not being discriminative enough, resulting in incomplete regions and irregular boundaries.

Building change detection for remote sensing images Change Detection +3

R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object

10 code implementations15 Aug 2019 Xue Yang, Junchi Yan, Ziming Feng, Tao He

Considering the shortcoming of feature misalignment in existing refined single-stage detector, we design a feature refinement module to improve detection performance by getting more accurate features.

object-detection Object Detection In Aerial Images

Comparison Network for One-Shot Conditional Object Detection

no code implementations4 Apr 2019 Tengfei Zhang, Yue Zhang, Xian Sun, Hao Sun, Menglong Yan, Xue Yang, Kun fu

A two-stage detector for OSCD is introduced to compare the extracted query and target features with the learnable metric to approach the optimized non-linear conditional probability.

Object object-detection +1

Multinomial Random Forest: Toward Consistency and Privacy-Preservation

no code implementations10 Mar 2019 Yiming Li, Jiawang Bai, Jiawei Li, Xue Yang, Yong Jiang, Chun Li, Shu-Tao Xia

Despite the impressive performance of random forests (RF), its theoretical properties have not been thoroughly understood.

General Classification

SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects

3 code implementations ICCV 2019 Xue Yang, Jirui Yang, Junchi Yan, Yue Zhang, Tengfei Zhang, Zhi Guo, Sun Xian, Kun fu

Specifically, a sampling fusion network is devised which fuses multi-layer feature with effective anchor sampling, to improve the sensitivity to small objects.

Ranked #48 on Object Detection In Aerial Images on DOTA (using extra training data)

object-detection Object Detection In Aerial Images

Position Detection and Direction Prediction for Arbitrary-Oriented Ships via Multitask Rotation Region Convolutional Neural Network

3 code implementations13 Jun 2018 Xue Yang, Hao Sun, Xian Sun, Menglong Yan, Zhi Guo, Kun fu

The complexity of application scenarios, the redundancy of detection region, and the difficulty of dense ship detection are all the main obstacles that limit the successful operation of traditional methods in ship detection.

Position

Automatic Ship Detection of Remote Sensing Images from Google Earth in Complex Scenes Based on Multi-Scale Rotation Dense Feature Pyramid Networks

4 code implementations12 Jun 2018 Xue Yang, Hao Sun, Kun fu, Jirui Yang, Xian Sun, Menglong Yan, Zhi Guo

Additionally, in the case of ship rotation and dense arrangement, we design a rotation anchor strategy to predict the minimum circumscribed rectangle of the object so as to reduce the redundant detection region and improve the recall.

object-detection Object Detection

Sequence-based Multimodal Apprenticeship Learning For Robot Perception and Decision Making

no code implementations24 Feb 2017 Fei Han, Xue Yang, Yu Zhang, Hao Zhang

Apprenticeship learning has recently attracted a wide attention due to its capability of allowing robots to learn physical tasks directly from demonstrations provided by human experts.

Decision Making

Simultaneous Feature and Body-Part Learning for Real-Time Robot Awareness of Human Behaviors

no code implementations24 Feb 2017 Fei Han, Xue Yang, Christopher Reardon, Yu Zhang, Hao Zhang

We formulate FABL as a regression-like optimization problem with structured sparsity-inducing norms to model interrelationships of body parts and features.

Enforcing Template Representability and Temporal Consistency for Adaptive Sparse Tracking

no code implementations30 Apr 2016 Xue Yang, Fei Han, Hua Wang, Hao Zhang

Sparse representation has been widely studied in visual tracking, which has shown promising tracking performance.

Descriptive Visual Tracking

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