720 citations · 810 across the 30 of their papers we have counts for
16 papers · 1 filter
Dynamic Multimodal Activation Steering for Hallucination Mitigation in Large Vision-Language Models
Jianghao Yin, Qin Chen, Kedi Chen +3
Large Vision-Language Models (LVLMs) exhibit outstanding performance on vision-language tasks but struggle with hallucination problems. Through in-depth analysis of LVLM activation…
CL-MoE: Enhancing Multimodal Large Language Model with Dual Momentum Mixture-of-Experts for Continual Visual Question Answering
Tianyu Huai, Jie Zhou, Xingjiao Wu +4
Multimodal large language models (MLLMs) have garnered widespread attention from researchers due to their remarkable understanding and generation capabilities in visual language ta…
MultiColor: Image Colorization by Learning from Multiple Color Spaces
Xiangcheng Du, Zhao Zhou, Yanlong Wang +3
Deep networks have shown impressive performance in the image restoration tasks, such as image colorization. However, we find that previous approaches rely on the digital representa…
Fine-Grained Scene Image Classification with Modality-Agnostic Adapter
Yiqun Wang, Zhao Zhou, Xiangcheng Du +3
When dealing with the task of fine-grained scene image classification, most previous works lay much emphasis on global visual features when doing multi-modal feature fusion. In oth…
UMAAF: Unveiling Aesthetics via Multifarious Attributes of Images
Weijie Li, Yitian Wan, Xingjiao Wu +3
With the increasing prevalence of smartphones and websites, Image Aesthetic Assessment (IAA) has become increasingly crucial. While the significance of attributes in IAA is widely…
DDT: Dual-branch Deformable Transformer for Image Denoising
Kangliang Liu, Xiangcheng Du, Sijie Liu +3
Transformer is beneficial for image denoising tasks since it can model long-range dependencies to overcome the limitations presented by inductive convolutional biases. However, dir…
LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusion
Xin Li, Tao Ma, Yuenan Hou +8
LiDAR-camera fusion methods have shown impressive performance in 3D object detection. Recent advanced multi-modal methods mainly perform global fusion, where image features and poi…
Homogeneous Multi-modal Feature Fusion and Interaction for 3D Object Detection
Xin Li, Botian Shi, Yuenan Hou +4
Multi-modal 3D object detection has been an active research topic in autonomous driving. Nevertheless, it is non-trivial to explore the cross-modal feature fusion between sparse 3D…
Progressive Scene Text Erasing with Self-Supervision
Xiangcheng Du, Zhao Zhou, Yingbin Zheng +3
Scene text erasing seeks to erase text contents from scene images and current state-of-the-art text erasing models are trained on large-scale synthetic data. Although data syntheti…
Cross-Domain Document Layout Analysis Using Document Style Guide
Xingjiao Wu, Luwei Xiao, Xiangcheng Du +5
The document layout analysis (DLA) aims to decompose document images into high-level semantic areas (i.e., figures, tables, texts, and background). Creating a DLA framework with st…
Document Layout Analysis with Aesthetic-Guided Image Augmentation
Tianlong Ma, Xingjiao Wu, Xin Li +4
Document layout analysis (DLA) plays an important role in information extraction and document understanding. At present, document layout analysis has reached a milestone achievemen…
Human-In-The-Loop Document Layout Analysis
Xingjiao Wu, Tianlong Ma, Xin Li +2
Document layout analysis (DLA) aims to divide a document image into different types of regions. DLA plays an important role in the document content understanding and information ex…
Document Layout Analysis via Dynamic Residual Feature Fusion
Xingjiao Wu, Ziling Hu, Xiangcheng Du +2
The document layout analysis (DLA) aims to split the document image into different interest regions and understand the role of each region, which has wide application such as optic…
Scene Text Recognition with Temporal Convolutional Encoder
Xiangcheng Du, Tianlong Ma, Yingbin Zheng +3
Texts from scene images typically consist of several characters and exhibit a characteristic sequence structure. Existing methods capture the structure with the sequence-to-sequenc…
Fast Video Crowd Counting with a Temporal Aware Network
Xingjiao Wu, Baohan Xu, Yingbin Zheng +3
Crowd counting aims to count the number of instantaneous people in a crowded space, and many promising solutions have been proposed for single image crowd counting. With the ubiqui…
Adaptive Scenario Discovery for Crowd Counting
Xingjiao Wu, Yingbin Zheng, Hao Ye +3
Crowd counting, i.e., estimation number of the pedestrian in crowd images, is emerging as an important research problem with the public security applications. A key component for t…