18 citations · 33 across the 7 of their papers we have counts for
7 papers
3DTMDet: A Dual-Path Synergy Network of Transformer and SSM for 3D Object Detection in Point Clouds
Bingwen Qiu, Yuan Liu, Junqi Bai +5
A fundamental challenge in point cloud object detection lies in the conflict between the extreme sparsity of distant points and the need for remote context understanding. The exist…
FSCM: Frequency-Enhanced Spatial-Spectral Coupled Mamba for Infrared Hyperspectral Image Colorization
Tingting Liu, Yuan Liu, Guiping Chen +2
Thermal infrared imaging is robust to illumination variations and smoke interference, making it important for all-weather perception. However, the lack of natural color and fine te…
FMC-DETR: Frequency-Decoupled Multi-Domain Coordination for Aerial-View Object Detection
Ben Liang, Hongguang Wei, Yuan Liu +4
Remote sensing object detection is a critical technology for real-world applications such as natural resource monitoring, traffic management, and UAV-based rescue. Detecting tiny o…
MTSIC: Multi-stage Transformer-based GAN for Spectral Infrared Image Colorization
Tingting Liu, Yuan Liu, Jinhui Tang +5
Thermal infrared (TIR) images, acquired through thermal radiation imaging, are unaffected by variations in lighting conditions and atmospheric haze. However, TIR images inherently…
Hyperspectral Image Super-Resolution via Dual-domain Network Based on Hybrid Convolution
Tingting Liu, Yuan Liu, Chuncheng Zhang +3
Since the number of incident energies is limited, it is difficult to directly acquire hyperspectral images (HSI) with high spatial resolution. Considering the high dimensionality a…
Gradient Domain Weighted Guided Image Filtering
Bo Wang, Yihong Wang, Xiubao Sui +2
Guided image filter is a well-known local filter in image processing. However, the presence of halo artifacts is a common issue associated with this type of filter. This paper prop…
Thermal Infrared Colorization via Conditional Generative Adversarial Network
Xiaodong Kuang, Xiubao Sui, Chengwei Liu +3
Transforming a thermal infrared image into a realistic RGB image is a challenging task. In this paper we propose a deep learning method to bridge this gap. We propose learning the…