15 citations · 15 across the 10 of their papers we have counts for
7 papers · 1 filter
LDFE: Laplacian Decoupled Feature Enhancement Block for Dual-Stream CNN-based RGB-IR Object Detection
Wenhao Dong, Xiaoyan Luo, Linlin Yang +4
The complementary information between RGB and IR images can significantly enhance object detection performance under extreme conditions. Existing methods prefer dual-stream CNN bac…
InfraNet: Quality-Aware RGB Guidance for Efficient Infrared Object Detection
Zichao Feng, Haodong Zhu, Jingying Yang +8
Robust object detection under adverse visual conditions remains a long-standing challenge for multi-modal perception systems. Existing fusion-based methods typically require both R…
UrbanGS: A Scalable and Efficient Architecture for Geometrically Accurate Large-Scene Reconstruction
Changbai Li, Haodong Zhu, Hanlin Chen +6
While 3D Gaussian Splatting (3DGS) enables high-quality, real-time rendering for bounded scenes, its extension to large-scale urban environments gives rise to critical challenges i…
PartDiffuser: Part-wise 3D Mesh Generation via Discrete Diffusion
Yichen Yang, Hong Li, Haodong Zhu +4
Existing autoregressive (AR) methods for generating artist-designed meshes struggle to balance global structural consistency with high-fidelity local details, and are susceptible t…
WaveMamba: Wavelet-Driven Mamba Fusion for RGB-Infrared Object Detection
Haodong Zhu, Wenhao Dong, Linlin Yang +10
Leveraging the complementary characteristics of visible (RGB) and infrared (IR) imagery offers significant potential for improving object detection. In this paper, we propose WaveM…
HRGS: Hierarchical Gaussian Splatting for Memory-Efficient High-Resolution 3D Reconstruction
Changbai Li, Haodong Zhu, Hanlin Chen +6
3D Gaussian Splatting (3DGS) has made significant strides in real-time 3D scene reconstruction, but faces memory scalability issues in high-resolution scenarios. To address this, w…
Fusion-Mamba for Cross-modality Object Detection
Wenhao Dong, Haodong Zhu, Shaohui Lin +6
Cross-modality fusing complementary information from different modalities effectively improves object detection performance, making it more useful and robust for a wider range of a…