57 citations · 252 across the 48 of their papers we have counts for
48 papers · 1 filter
BladeYOLO: Wind Turbine Blade Defect Detection with Limited Annotations and Weak-Saliency Awareness
Yabin Xu, Fangtao Zhang, Fan Wang +5
Wind turbine blade defect detection remains highly challenging in real-world inspection scenarios due to limited on-site data and the subtle visual characteristics of defects. In p…
FriendNet: Detection-Friendly Dehazing Network
Yihua Fan, Yongzhen Wang, Mingqiang Wei +2
Adverse weather conditions often impair the quality of captured images, inevitably inducing cutting-edge object detection models for advanced driver assistance systems (ADAS) and a…
Cross-BERT for Point Cloud Pretraining
Xin Li, Peng Li, Zeyong Wei +7
Introducing BERT into cross-modal settings raises difficulties in its optimization for handling multiple modalities. Both the BERT architecture and training objective need to be ad…
SVDFormer: Complementing Point Cloud via Self-view Augmentation and Self-structure Dual-generator
Zhe Zhu, Honghua Chen, Xing He +3
In this paper, we propose a novel network, SVDFormer, to tackle two specific challenges in point cloud completion: understanding faithful global shapes from incomplete point clouds…
Don't worry about mistakes! Glass Segmentation Network via Mistake Correction
Chengyu Zheng, Peng Li, Xiao-Ping Zhang +2
Recall one time when we were in an unfamiliar mall. We might mistakenly think that there exists or does not exist a piece of glass in front of us. Such mistakes will remind us to w…
Joint Depth Estimation and Mixture of Rain Removal From a Single Image
Yongzhen Wang, Xuefeng Yan, Yanbiao Niu +3
Rainy weather significantly deteriorates the visibility of scene objects, particularly when images are captured through outdoor camera lenses or windshields. Through careful observ…
Search By Image: Deeply Exploring Beneficial Features for Beauty Product Retrieval
Mingqiang Wei, Qian Sun, Haoran Xie +2
Searching by image is popular yet still challenging due to the extensive interference arose from i) data variations (e.g., background, pose, visual angle, brightness) of real-world…
PointGame: Geometrically and Adaptively Masked Auto-Encoder on Point Clouds
Yun Liu, Xuefeng Yan, Zhilei Chen +3
Self-supervised learning is attracting large attention in point cloud understanding. However, exploring discriminative and transferable features still remains challenging due to th…
ProxyFormer: Proxy Alignment Assisted Point Cloud Completion with Missing Part Sensitive Transformer
Shanshan Li, Pan Gao, Xiaoyang Tan +1
Problems such as equipment defects or limited viewpoints will lead the captured point clouds to be incomplete. Therefore, recovering the complete point clouds from the partial ones…
PointSmile: Point Self-supervised Learning via Curriculum Mutual Information
Xin Li, Mingqiang Wei, Songcan Chen
Self-supervised learning is attracting wide attention in point cloud processing. However, it is still not well-solved to gain discriminative and transferable features of point clou…
Rethinking Real-world Image Deraining via An Unpaired Degradation-Conditioned Diffusion Model
Yiyang Shen, Mingqiang Wei, Yongzhen Wang +2
Recent diffusion models have exhibited great potential in generative modeling tasks. Part of their success can be attributed to the ability of training stable on huge sets of paire…
ImLiDAR: Cross-Sensor Dynamic Message Propagation Network for 3D Object Detection
Yiyang Shen, Rongwei Yu, Peng Wu +4
LiDAR and camera, as two different sensors, supply geometric (point clouds) and semantic (RGB images) information of 3D scenes. However, it is still challenging for existing method…
PointSee: Image Enhances Point Cloud
Lipeng Gu, Xuefeng Yan, Peng Cui +5
There is a trend to fuse multi-modal information for 3D object detection (3OD). However, the challenging problems of low lightweightness, poor flexibility of plug-and-play, and ina…
Semi-UFormer: Semi-supervised Uncertainty-aware Transformer for Image Dehazing
Ming Tong, Yongzhen Wang, Peng Cui +2
Image dehazing is fundamental yet not well-solved in computer vision. Most cutting-edge models are trained in synthetic data, leading to the poor performance on real-world hazy sce…
LBF:Learnable Bilateral Filter For Point Cloud Denoising
Huajian Si, Zeyong Wei, Zhe Zhu +4
Bilateral filter (BF) is a fast, lightweight and effective tool for image denoising and well extended to point cloud denoising. However, it often involves continual yet manual para…
PSFormer: Point Transformer for 3D Salient Object Detection
Baian Chen, Lipeng Gu, Xin Zhuang +3
We propose PSFormer, an effective point transformer model for 3D salient object detection. PSFormer is an encoder-decoder network that takes full advantage of transformers to model…
GeoGCN: Geometric Dual-domain Graph Convolution Network for Point Cloud Denoising
Zhaowei Chen, Peng Li, Zeyong Wei +4
We propose GeoGCN, a novel geometric dual-domain graph convolution network for point cloud denoising (PCD). Beyond the traditional wisdom of PCD, to fully exploit the geometric inf…
iSmallNet: Densely Nested Network with Label Decoupling for Infrared Small Target Detection
Zhiheng Hu, Yongzhen Wang, Peng Li +3
Small targets are often submerged in cluttered backgrounds of infrared images. Conventional detectors tend to generate false alarms, while CNN-based detectors lose small targets in…
SPCNet: Stepwise Point Cloud Completion Network
Fei Hu, Honghua Chen, Xuequan Lu +5
How will you repair a physical object with large missings? You may first recover its global yet coarse shape and stepwise increase its local details. We are motivated to imitate th…
TogetherNet: Bridging Image Restoration and Object Detection Together via Dynamic Enhancement Learning
Yongzhen Wang, Xuefeng Yan, Kaiwen Zhang +4
Adverse weather conditions such as haze, rain, and snow often impair the quality of captured images, causing detection networks trained on normal images to generalize poorly in the…
Contrastive Semantic-Guided Image Smoothing Network
Jie Wang, Yongzhen Wang, Yidan Feng +5
Image smoothing is a fundamental low-level vision task that aims to preserve salient structures of an image while removing insignificant details. Deep learning has been explored in…
MODNet: Multi-offset Point Cloud Denoising Network Customized for Multi-scale Patches
Anyi Huang, Qian Xie, Zhoutao Wang +3
The intricacy of 3D surfaces often results cutting-edge point cloud denoising (PCD) models in surface degradation including remnant noise, wrongly-removed geometric details. Althou…
UTOPIC: Uncertainty-aware Overlap Prediction Network for Partial Point Cloud Registration
Zhilei Chen, Honghua Chen, Lina Gong +5
High-confidence overlap prediction and accurate correspondences are critical for cutting-edge models to align paired point clouds in a partial-to-partial manner. However, there inh…
3DLG-Detector: 3D Object Detection via Simultaneous Local-Global Feature Learning
Baian Chen, Liangliang Nan, Haoran Xie +3
Capturing both local and global features of irregular point clouds is essential to 3D object detection (3OD). However, mainstream 3D detectors, e.g., VoteNet and its variants, eith…