8 citations · 21 across the 18 of their papers we have counts for
18 papers
RU4D-SLAM: Reweighting Uncertainty in Gaussian Splatting SLAM for 4D Scene Reconstruction
Yangfan Zhao, Hanwei Zhang, Ke Huang +3
Combining 3D Gaussian splatting with Simultaneous Localization and Mapping (SLAM) has gained popularity as it enables continuous 3D environment reconstruction during motion. Howeve…
BFANet: Revisiting 3D Semantic Segmentation with Boundary Feature Analysis
Weiguang Zhao, Rui Zhang, Qiufeng Wang +2
3D semantic segmentation plays a fundamental and crucial role to understand 3D scenes. While contemporary state-of-the-art techniques predominantly concentrate on elevating the ove…
IDEA: Image Description Enhanced CLIP-Adapter
Zhipeng Ye, Feng Jiang, Qiufeng Wang +2
CLIP (Contrastive Language-Image Pre-training) has attained great success in pattern recognition and computer vision. Transferring CLIP to downstream tasks (e.g. zero- or few-shot…
Un-mixing Test-time Adaptation under Heterogeneous Data Streams
Zixian Su, Jingwei Guo, Xi Yang +2
Deploying deep models in real-world scenarios remains challenging due to significant performance drops under distribution shifts between training and deployment environments. Test-…
Is Your Model Really A Good Math Reasoner? Evaluating Mathematical Reasoning with Checklist
Zihao Zhou, Shudong Liu, Maizhen Ning +6
Exceptional mathematical reasoning ability is one of the key features that demonstrate the power of large language models (LLMs). How to comprehensively define and evaluate the mat…
Polar-Doc: One-Stage Document Dewarping with Multi-Scope Constraints under Polar Representation
Weiguang Zhang, Qiufeng Wang, Kaizhu Huang
Document dewarping, aiming to eliminate geometric deformation in photographed documents to benefit text recognition, has made great progress in recent years but is still far from b…
Unraveling Batch Normalization for Realistic Test-Time Adaptation
Zixian Su, Jingwei Guo, Kai Yao +3
While recent test-time adaptations exhibit efficacy by adjusting batch normalization to narrow domain disparities, their effectiveness diminishes with realistic mini-batches due to…
Context Does Matter: End-to-end Panoptic Narrative Grounding with Deformable Attention Refined Matching Network
Yiming Lin, Xiao-Bo Jin, Qiufeng Wang +1
Panoramic Narrative Grounding (PNG) is an emerging visual grounding task that aims to segment visual objects in images based on dense narrative captions. The current state-of-the-a…
ShanshuiDaDA: An Interactive, Generative System towards Chinese Shanshui Painting
Aven Le Zhou, Qiufeng Wang, Cheng-Hung Lo +1
Shanshui, which means mountain and water, is an East Asian traditional brush painting involving natural landscapes. This paper proposes an interactive and generative system based o…
A Symbolic Character-Aware Model for Solving Geometry Problems
Maizhen Ning, Qiu-Feng Wang, Kaizhu Huang +1
AI has made significant progress in solving math problems, but geometry problems remain challenging due to their reliance on both text and diagrams. In the text description, symbol…
Learning by Analogy: Diverse Questions Generation in Math Word Problem
Zihao Zhou, Maizhen Ning, Qiufeng Wang +4
Solving math word problem (MWP) with AI techniques has recently made great progress with the success of deep neural networks (DNN), but it is far from being solved. We argue that t…
SaliencyCut: Augmenting Plausible Anomalies for Anomaly Detection
Jianan Ye, Yijie Hu, Xi Yang +3
Anomaly detection under open-set scenario is a challenging task that requires learning discriminative fine-grained features to detect anomalies that were even unseen during trainin…
Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image Segmentation
Zixian Su, Kai Yao, Xi Yang +3
Single-source domain generalization (SDG) in medical image segmentation is a challenging yet essential task as domain shifts are quite common among clinical image datasets. Previou…
SSD: Towards Better Text-Image Consistency Metric in Text-to-Image Generation
Zhaorui Tan, Xi Yang, Zihan Ye +4
Generating consistent and high-quality images from given texts is essential for visual-language understanding. Although impressive results have been achieved in generating high-qua…
Mind The Gap: Alleviating Local Imbalance for Unsupervised Cross-Modality Medical Image Segmentation
Zixian Su, Kai Yao, Xi Yang +4
Unsupervised cross-modality medical image adaptation aims to alleviate the severe domain gap between different imaging modalities without using the target domain label. A key in th…
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies
Zhuang Qian, Kaizhu Huang, Qiu-Feng Wang +1
In the last a few decades, deep neural networks have achieved remarkable success in machine learning, computer vision, and pattern recognition. Recent studies however show that neu…
Improving Model Robustness with Latent Distribution Locally and Globally
Zhuang Qian, Shufei Zhang, Kaizhu Huang +3
In this work, we consider model robustness of deep neural networks against adversarial attacks from a global manifold perspective. Leveraging both the local and global latent infor…
Generative Adversarial Classifier for Handwriting Characters Super-Resolution
Zhuang Qian, Kaizhu Huang, Qiufeng Wang +2
Generative Adversarial Networks (GAN) receive great attentions recently due to its excellent performance in image generation, transformation, and super-resolution. However, GAN has…