318 citations · 1.1k across the 52 of their papers we have counts for
14 papers · 1 filter
Traffic Image Restoration under Adverse Weather via Frequency-Aware Mamba
Liwen Pan, Longguang Wang, Guangwei Gao +3
Traffic image restoration under adverse weather conditions remains a critical challenge for intelligent transportation systems. Existing methods primarily focus on spatial-domain m…
Bidirectional Feature-aligned Motion Transformation for Efficient Dynamic Point Cloud Compression
Xuan Deng, Xingtao Wang, Xiandong Meng +4
Efficient dynamic point cloud compression (DPCC) critically depends on accurate motion estimation and compensation. However, the inherently irregular structure and substantial loca…
Deep Lookup Network
Yulan Guo, Longguang Wang, Wendong Mao +4
Convolutional neural networks are constructed with massive operations with different types and are highly computationally intensive. Among these operations, multiplication operatio…
UPGS: Unified Pose-aware Gaussian Splatting for Dynamic Scene Deblurring
Zhijing Wu, Longguang Wang
Reconstructing dynamic 3D scenes from monocular video has broad applications in AR/VR, robotics, and autonomous navigation, but often fails due to severe motion blur caused by came…
PanMatch: Unleashing the Potential of Large Vision Models for Unified Matching Models
Yongjian Zhang, Longguang Wang, Kunhong Li +4
This work presents PanMatch, a versatile foundation model for robust correspondence matching. Unlike previous methods that rely on task-specific architectures and domain-specific f…
Learning Robust Stereo Matching in the Wild with Selective Mixture-of-Experts
Yun Wang, Longguang Wang, Chenghao Zhang +6
Recently, learning-based stereo matching networks have advanced significantly. However, they often lack robustness and struggle to achieve impressive cross-domain performance due t…
Probing Deep into Temporal Profile Makes the Infrared Small Target Detector Much Better
Ruojing Li, Wei An, Yingqian Wang +6
Infrared small target (IRST) detection is challenging in simultaneously achieving precise, robust, and efficient performance due to extremely dim targets and strong interference. C…
A Unified Hierarchical Framework for Fine-grained Cross-view Geo-localization over Large-scale Scenarios
Zhuo Song, Ye Zhang, Kunhong Li +2
Cross-view geo-localization is a promising solution for large-scale localization problems, requiring the sequential execution of retrieval and metric localization tasks to achieve…
DropoutGS: Dropping Out Gaussians for Better Sparse-view Rendering
Yexing Xu, Longguang Wang, Minglin Chen +3
Although 3D Gaussian Splatting (3DGS) has demonstrated promising results in novel view synthesis, its performance degrades dramatically with sparse inputs and generates undesirable…
Pluggable Style Representation Learning for Multi-Style Transfer
Hongda Liu, Longguang Wang, Weijun Guan +2
Due to the high diversity of image styles, the scalability to various styles plays a critical role in real-world applications. To accommodate a large amount of styles, previous mul…
SaMam: Style-aware State Space Model for Arbitrary Image Style Transfer
Hongda Liu, Longguang Wang, Ye Zhang +2
Global effective receptive field plays a crucial role for image style transfer (ST) to obtain high-quality stylized results. However, existing ST backbones (e.g., CNNs and Transfor…
Simulating the Real World: A Unified Survey of Multimodal Generative Models
Yuqi Hu, Longguang Wang, Xian Liu +7
Understanding and replicating the real world is a critical challenge in Artificial General Intelligence (AGI) research. To achieve this, many existing approaches, such as world mod…
AIQViT: Architecture-Informed Post-Training Quantization for Vision Transformers
Runqing Jiang, Ye Zhang, Longguang Wang +2
Post-training quantization (PTQ) has emerged as a promising solution for reducing the storage and computational cost of vision transformers (ViTs). Recent advances primarily target…
Layout2Scene: 3D Semantic Layout Guided Scene Generation via Geometry and Appearance Diffusion Priors
Minglin Chen, Longguang Wang, Sheng Ao +3
3D scene generation conditioned on text prompts has significantly progressed due to the development of 2D diffusion generation models. However, the textual description of 3D scenes…