353 citations · 1.5k across the 84 of their papers we have counts for
86 papers
Hi-SAM: Marrying Segment Anything Model for Hierarchical Text Segmentation
Maoyuan Ye, Jing Zhang, Juhua Liu +5
The Segment Anything Model (SAM), a profound vision foundation model pretrained on a large-scale dataset, breaks the boundaries of general segmentation and sparks various downstrea…
GoMatching: A Simple Baseline for Video Text Spotting via Long and Short Term Matching
Haibin He, Maoyuan Ye, Jing Zhang +3
Beyond the text detection and recognition tasks in image text spotting, video text spotting presents an augmented challenge with the inclusion of tracking. While advanced end-to-en…
Unified Domain Adaptive Semantic Segmentation
Zhe Zhang, Gaochang Wu, Jing Zhang +3
Unsupervised Domain Adaptive Semantic Segmentation (UDA-SS) aims to transfer the supervision from a labeled source domain to an unlabeled target domain. The majority of existing UD…
Cross-modal & Cross-domain Learning for Unsupervised LiDAR Semantic Segmentation
Yiyang Chen, Shanshan Zhao, Changxing Ding +3
In recent years, cross-modal domain adaptation has been studied on the paired 2D image and 3D LiDAR data to ease the labeling costs for 3D LiDAR semantic segmentation (3DLSS) in th…
Patch-Wise Point Cloud Generation: A Divide-and-Conquer Approach
Cheng Wen, Baosheng Yu, Rao Fu +1
A generative model for high-fidelity point clouds is of great importance in synthesizing 3d environments for applications such as autonomous driving and robotics. Despite the recen…
Human-imperceptible, Machine-recognizable Images
Fusheng Hao, Fengxiang He, Yikai Wang +4
Massive human-related data is collected to train neural networks for computer vision tasks. A major conflict is exposed relating to software engineers between better developing AI…
Towards Open Vocabulary Learning: A Survey
Jianzong Wu, Xiangtai Li, Shilin Xu +9
In the field of visual scene understanding, deep neural networks have made impressive advancements in various core tasks like segmentation, tracking, and detection. However, most a…
Multi-Granularity Hand Action Detection
Ting Zhe, Jing Zhang, Yongqian Li +3
Detecting hand actions in videos is crucial for understanding video content and has diverse real-world applications. Existing approaches often focus on whole-body actions or coarse…
Collect-and-Distribute Transformer for 3D Point Cloud Analysis
Haibo Qiu, Baosheng Yu, Dacheng Tao
Remarkable advancements have been made recently in point cloud analysis through the exploration of transformer architecture, but it remains challenging to effectively learn local a…
Cocktail: Mixing Multi-Modality Controls for Text-Conditional Image Generation
Minghui Hu, Jianbin Zheng, Daqing Liu +4
Text-conditional diffusion models are able to generate high-fidelity images with diverse contents. However, linguistic representations frequently exhibit ambiguous descriptions of…
MMoT: Mixture-of-Modality-Tokens Transformer for Composed Multimodal Conditional Image Synthesis
Jianbin Zheng, Daqing Liu, Chaoyue Wang +4
Existing multimodal conditional image synthesis (MCIS) methods generate images conditioned on any combinations of various modalities that require all of them must be exactly confor…
Scalable Mask Annotation for Video Text Spotting
Haibin He, Jing Zhang, Mengyang Xu +3
Video text spotting refers to localizing, recognizing, and tracking textual elements such as captions, logos, license plates, signs, and other forms of text within consecutive vide…
All Points Matter: Entropy-Regularized Distribution Alignment for Weakly-supervised 3D Segmentation
Liyao Tang, Zhe Chen, Shanshan Zhao +2
Pseudo-labels are widely employed in weakly supervised 3D segmentation tasks where only sparse ground-truth labels are available for learning. Existing methods often rely on empiri…
SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model
Di Wang, Jing Zhang, Bo Du +4
The success of the Segment Anything Model (SAM) demonstrates the significance of data-centric machine learning. However, due to the difficulties and high costs associated with anno…
Empowering Agrifood System with Artificial Intelligence: A Survey of the Progress, Challenges and Opportunities
Tao Chen, Liang Lv, Di Wang +12
With the world population rapidly increasing, transforming our agrifood systems to be more productive, efficient, safe, and sustainable is crucial to mitigate potential food shorta…
Compositional 3D Human-Object Neural Animation
Zhi Hou, Baosheng Yu, Dacheng Tao
Human-object interactions (HOIs) are crucial for human-centric scene understanding applications such as human-centric visual generation, AR/VR, and robotics. Since existing methods…
Segment Anything in Non-Euclidean Domains: Challenges and Opportunities
Yongcheng Jing, Xinchao Wang, Dacheng Tao
The recent work known as Segment Anything (SA) has made significant strides in pushing the boundaries of semantic segmentation into the era of foundation models. The impact of SA h…
DCN-T: Dual Context Network with Transformer for Hyperspectral Image Classification
Di Wang, Jing Zhang, Bo Du +2
Hyperspectral image (HSI) classification is challenging due to spatial variability caused by complex imaging conditions. Prior methods suffer from limited representation ability, a…
UVA: Towards Unified Volumetric Avatar for View Synthesis, Pose rendering, Geometry and Texture Editing
Jinlong Fan, Jing Zhang, Dacheng Tao
Neural radiance field (NeRF) has become a popular 3D representation method for human avatar reconstruction due to its high-quality rendering capabilities, e.g., regarding novel vie…
Deep Image Matting: A Comprehensive Survey
Jizhizi Li, Jing Zhang, Dacheng Tao
Image matting refers to extracting precise alpha matte from natural images, and it plays a critical role in various downstream applications, such as image editing. Despite being an…
Event-based Simultaneous Localization and Mapping: A Comprehensive Survey
Kunping Huang, Sen Zhang, Jing Zhang +1
In recent decades, visual simultaneous localization and mapping (vSLAM) has gained significant interest in both academia and industry. It estimates camera motion and reconstructs t…
Vision Transformer with Quadrangle Attention
Qiming Zhang, Jing Zhang, Yufei Xu +1
Window-based attention has become a popular choice in vision transformers due to its superior performance, lower computational complexity, and less memory footprint. However, the d…
SimDistill: Simulated Multi-modal Distillation for BEV 3D Object Detection
Haimei Zhao, Qiming Zhang, Shanshan Zhao +3
Multi-view camera-based 3D object detection has become popular due to its low cost, but accurately inferring 3D geometry solely from camera data remains challenging and may lead to…
Deep Learning for Camera Calibration and Beyond: A Survey
Kang Liao, Lang Nie, Shujuan Huang +5
Camera calibration involves estimating camera parameters to infer geometric features from captured sequences, which is crucial for computer vision and robotics. However, convention…