Search Results for author: Zhenjun Han

Found 23 papers, 13 papers with code

CPR++: Object Localization via Single Coarse Point Supervision

2 code implementations30 Jan 2024 Xuehui Yu, Pengfei Chen, Kuiran Wang, Xumeng Han, Guorong Li, Zhenjun Han, Qixiang Ye, Jianbin Jiao

CPR reduces the semantic variance by selecting a semantic centre point in a neighbourhood region to replace the initial annotated point.

Object Object Localization

P2Seg: Pointly-supervised Segmentation via Mutual Distillation

no code implementations18 Jan 2024 Zipeng Wang, Xuehui Yu, Xumeng Han, Wenwen Yu, Zhixun Huang, Jianbin Jiao, Zhenjun Han

Nevertheless, weakly supervised semantic segmentation methods are proficient in utilizing intra-class feature consistency to capture the boundary contours of the same semantic regions.

Box-supervised Instance Segmentation Segmentation +2

Weakly Supervised Video Individual CountingWeakly Supervised Video Individual Counting

1 code implementation10 Dec 2023 Xinyan Liu, Guorong Li, Yuankai Qi, Ziheng Yan, Zhenjun Han, Anton Van Den Hengel, Ming-Hsuan Yang, Qingming Huang

% To provide a more realistic reflection of the underlying practical challenge, we introduce a weakly supervised VIC task, wherein trajectory labels are not provided.

Contrastive Learning Video Individual Counting

Boosting Segment Anything Model Towards Open-Vocabulary Learning

1 code implementation6 Dec 2023 Xumeng Han, Longhui Wei, Xuehui Yu, Zhiyang Dou, Xin He, Kuiran Wang, Zhenjun Han, Qi Tian

The recent Segment Anything Model (SAM) has emerged as a new paradigmatic vision foundation model, showcasing potent zero-shot generalization and flexible prompting.

Object Object Localization +2

P2RBox: A Single Point is All You Need for Oriented Object Detection

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 the P2RBox network, which leverages point annotations and a mask generator to create mask proposals, followed by filtration through our Inspector Module and Constrainer Module.

Object object-detection +2

Spatial Self-Distillation for Object Detection with Inaccurate Bounding Boxes

1 code implementation ICCV 2023 Di wu, Pengfei Chen, Xuehui Yu, Guorong Li, Zhenjun Han, Jianbin Jiao

Object detection via inaccurate bounding boxes supervision has boosted a broad interest due to the expensive high-quality annotation data or the occasional inevitability of low annotation quality (\eg tiny objects).

Multiple Instance Learning Object +2

CircleNet: Reciprocating Feature Adaptation for Robust Pedestrian Detection

no code implementations12 Dec 2022 Tianliang Zhang, Zhenjun Han, Huijuan Xu, Baochang Zhang, Qixiang Ye

In this paper we propose a novel feature learning model, referred to as CircleNet, to achieve feature adaptation by mimicking the process humans looking at low resolution and occluded objects: focusing on it again, at a finer scale, if the object can not be identified clearly for the first time.

object-detection Object Detection +1

Multi-Attention Network for Compressed Video Referring Object Segmentation

1 code implementation26 Jul 2022 Weidong Chen, Dexiang Hong, Yuankai Qi, Zhenjun Han, Shuhui Wang, Laiyun Qing, Qingming Huang, Guorong Li

To address this problem, we propose a multi-attention network which consists of dual-path dual-attention module and a query-based cross-modal Transformer module.

Object Referring Expression Segmentation +4

Object Localization under Single Coarse Point Supervision

2 code implementations CVPR 2022 Xuehui Yu, Pengfei Chen, Di wu, Najmul Hassan, Guorong Li, Junchi Yan, Humphrey Shi, Qixiang Ye, Zhenjun Han

In this study, we propose a POL method using coarse point annotations, relaxing the supervision signals from accurate key points to freely spotted points.

Multiple Instance Learning Object +1

P2P-Loc: Point to Point Tiny Person Localization

no code implementations31 Dec 2021 Xuehui Yu, Di wu, Qixiang Ye, Jianbin Jiao, Zhenjun Han

As a result, we propose a point self-refinement approach that iteratively updates point annotations in a self-paced way.

Object Object Localization

Rethinking Sampling Strategies for Unsupervised Person Re-identification

2 code implementations7 Jul 2021 Xumeng Han, Xuehui Yu, Guorong Li, Jian Zhao, Gang Pan, Qixiang Ye, Jianbin Jiao, Zhenjun Han

While extensive research has focused on the framework design and loss function, this paper shows that sampling strategy plays an equally important role.

Pseudo Label Representation Learning +1

SM+: Refined Scale Match for Tiny Person Detection

no code implementations6 Feb 2021 Nan Jiang, Xuehui Yu, Xiaoke Peng, Yuqi Gong, Zhenjun Han

Detecting tiny objects ( e. g., less than 20 x 20 pixels) in large-scale images is an important yet open problem.

Human Detection

Anti-UAV: A Large Multi-Modal Benchmark for UAV Tracking

1 code implementation21 Jan 2021 Nan Jiang, Kuiran Wang, Xiaoke Peng, Xuehui Yu, Qiang Wang, Junliang Xing, Guorong Li, Jian Zhao, Guodong Guo, Zhenjun Han

The releasing of such a large-scale dataset could be a useful initial step in research of tracking UAVs.

Exploiting Sample Correlation for Crowd Counting With Multi-Expert Network

no code implementations ICCV 2021 Xinyan Liu, Guorong Li, Zhenjun Han, Weigang Zhang, Yifan Yang, Qingming Huang, Nicu Sebe

Specifically, we propose a task-driven similarity metric based on sample's mutual enhancement, referred as co-fine-tune similarity, which can find a more efficient subset of data for training the expert network.

Crowd Counting

Effective Fusion Factor in FPN for Tiny Object Detection

no code implementations4 Nov 2020 Yuqi Gong, Xuehui Yu, Yao Ding, Xiaoke Peng, Jian Zhao, Zhenjun Han

We propose a novel concept, fusion factor, to control information that deep layers deliver to shallow layers, for adapting FPN to tiny object detection.

Object object-detection +1

The 1st Tiny Object Detection Challenge:Methods and Results

1 code implementation16 Sep 2020 Xuehui Yu, Zhenjun Han, Yuqi Gong, Nan Jiang, Jian Zhao, Qixiang Ye, Jie Chen, Yuan Feng, Bin Zhang, Xiaodi Wang, Ying Xin, Jingwei Liu, Mingyuan Mao, Sheng Xu, Baochang Zhang, Shumin Han, Cheng Gao, Wei Tang, Lizuo Jin, Mingbo Hong, Yuchao Yang, Shuiwang Li, Huan Luo, Qijun Zhao, Humphrey Shi

The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a current focus on tiny person detection.

Human Detection Object +2

Scale Match for Tiny Person Detection

2 code implementations23 Dec 2019 Xuehui Yu, Yuqi Gong, Nan Jiang, Qixiang Ye, Zhenjun Han

In this paper, we introduce a new benchmark, referred to as TinyPerson, opening up a promising directionfor tiny object detection in a long distance and with mas-sive backgrounds.

Human Detection Object +2

Min-Entropy Latent Model for Weakly Supervised Object Detection

1 code implementation CVPR 2018 Fang Wan, Pengxu Wei, Zhenjun Han, Jianbin Jiao, Qixiang Ye

Weakly supervised object detection is a challenging task when provided with image category supervision but required to learn, at the same time, object locations and object detectors.

Image Classification Object +3

A scalable convolutional neural network for task-specified scenarios via knowledge distillation

no code implementations19 Sep 2016 Mengnan Shi, Fei Qin, Qixiang Ye, Zhenjun Han, Jianbin Jiao

In this paper, we explore the redundancy in convolutional neural network, which scales with the complexity of vision tasks.

Knowledge Distillation

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