108 citations · 268 across the 19 of their papers we have counts for
19 papers · 1 filter
WeatherGen: A Unified Diverse Weather Generator for LiDAR Point Clouds via Spider Mamba Diffusion
Yang Wu, Yun Zhu, Kaihua Zhang +3
3D scene perception demands a large amount of adverse-weather LiDAR data, yet the cost of LiDAR data collection presents a significant scaling-up challenge. To this end, a series o…
Text2LiDAR: Text-guided LiDAR Point Cloud Generation via Equirectangular Transformer
Yang Wu, Kaihua Zhang, Jianjun Qian +2
The complex traffic environment and various weather conditions make the collection of LiDAR data expensive and challenging. Achieving high-quality and controllable LiDAR data gener…
Shifting Spotlight for Co-supervision: A Simple yet Efficient Single-branch Network to See Through Camouflage
Yang Hu, Jinxia Zhang, Kaihua Zhang +4
Camouflaged object detection (COD) remains a challenging task in computer vision. Existing methods often resort to additional branches for edge supervision, incurring substantial c…
Towards Open-World Co-Salient Object Detection with Generative Uncertainty-aware Group Selective Exchange-Masking
Yang Wu, Shenglong Hu, Huihui Song +3
The traditional definition of co-salient object detection (CoSOD) task is to segment the common salient objects in a group of relevant images. This definition is based on an assump…
Learning Self-Supervised Low-Rank Network for Single-Stage Weakly and Semi-Supervised Semantic Segmentation
Junwen Pan, Pengfei Zhu, Kaihua Zhang +5
Semantic segmentation with limited annotations, such as weakly supervised semantic segmentation (WSSS) and semi-supervised semantic segmentation (SSSS), is a challenging task that…
Learning Dynamic Compact Memory Embedding for Deformable Visual Object Tracking
Pengfei Zhu, Hongtao Yu, Kaihua Zhang +5
Recently, template-based trackers have become the leading tracking algorithms with promising performance in terms of efficiency and accuracy. However, the correlation operation bet…
Learning Spatio-Appearance Memory Network for High-Performance Visual Tracking
Fei Xie, Wankou Yang, Bo Liu +3
Existing visual object tracking usually learns a bounding-box based template to match the targets across frames, which cannot accurately learn a pixel-wise representation, thereby…
Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency Detection
Kaihua Zhang, Tengpeng Li, Shiwen Shen +3
Co-saliency detection aims to discover the common and salient foregrounds from a group of relevant images. For this task, we present a novel adaptive graph convolutional network wi…
Dual Temporal Memory Network for Efficient Video Object Segmentation
Kaihua Zhang, Long Wang, Dong Liu +3
Video Object Segmentation (VOS) is typically formulated in a semi-supervised setting. Given the ground-truth segmentation mask on the first frame, the task of VOS is to track and s…
Video Saliency Prediction Using Enhanced Spatiotemporal Alignment Network
Jin Chen, Huihui Song, Kaihua Zhang +2
Due to a variety of motions across different frames, it is highly challenging to learn an effective spatiotemporal representation for accurate video saliency prediction (VSP). To a…
Deep Object Co-segmentation via Spatial-Semantic Network Modulation
Kaihua Zhang, Jin Chen, Bo Liu +1
Object co-segmentation is to segment the shared objects in multiple relevant images, which has numerous applications in computer vision. This paper presents a spatial and semantic…
Unsupervised Video Segmentation via Spatio-Temporally Nonlocal Appearance Learning
Kaihua Zhang, Xuejun Li, Qingshan Liu
Video object segmentation is challenging due to the factors like rapidly fast motion, cluttered backgrounds, arbitrary object appearance variation and shape deformation. Most exist…
An Efficient Algorithm for the Piecewise-Smooth Model with Approximately Explicit Solutions
Huihui Song, Yuhui Zheng, Kaihua Zhang
This paper presents an efficient approach to image segmentation that approximates the piecewise-smooth (PS) functional in [12] with explicit solutions. By rendering some rational c…
Visual Tracking via Boolean Map Representations
Kaihua Zhang, Qingshan Liu, Ming-Hsuan Yang
In this paper, we present a simple yet effective Boolean map based representation that exploits connectivity cues for visual tracking. We describe a target object with histogram of…
Adaptive Compressive Tracking via Online Vector Boosting Feature Selection
Qingshan Liu, Jing Yang, Kaihua Zhang +1
Recently, the compressive tracking (CT) method has attracted much attention due to its high efficiency, but it cannot well deal with the large scale target appearance variations du…
Robust Visual Tracking via Convolutional Networks
Kaihua Zhang, Qingshan Liu, Yi Wu +1
Deep networks have been successfully applied to visual tracking by learning a generic representation offline from numerous training images. However the offline training is time-con…
Fast Tracking via Spatio-Temporal Context Learning
Kaihua Zhang, Lei Zhang, Ming-Hsuan Yang +1
In this paper, we present a simple yet fast and robust algorithm which exploits the spatio-temporal context for visual tracking. Our approach formulates the spatio-temporal relatio…
A Local Active Contour Model for Image Segmentation with Intensity Inhomogeneity
Kaihua Zhang, Lei Zhang, Kin-Man Lam +1
A novel locally statistical active contour model (ACM) for image segmentation in the presence of intensity inhomogeneity is presented in this paper. The inhomogeneous objects are m…
Re-initialization Free Level Set Evolution via Reaction Diffusion
Kaihua Zhang, Lei Zhang, Huihui Song +1
This paper presents a novel reaction-diffusion (RD) method for implicit active contours, which is completely free of the costly re-initialization procedure in level set evolution (…