15 citations · 17 across the 7 of their papers we have counts for
8 papers
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…
Teaching Vision-Language-Action Models What to See and Where to Look
Yuguang Yang, Canyu Chen, Zhewen Tan +10
Vision-Language-Action (VLA) models have emerged as a promising paradigm for end-to-end autonomous driving. However, existing VLAs' training relies heavily on text-centric visual q…
Learning domain-invariant features through channel-level sparsification for Out-Of Distribution Generalization
Haoran Pei, Yuguang Yang, Kexin Liu +2
Out-of-Distribution (OOD) generalization has become a primary metric for evaluating image analysis systems. Since deep learning models tend to capture domain-specific context, they…
Squeeze10-LLM: Squeezing LLMs' Weights by 10 Times via a Staged Mixed-Precision Quantization Method
Qingcheng Zhu, Yangyang Ren, Linlin Yang +6
Deploying large language models (LLMs) is challenging due to their massive parameters and high computational costs. Ultra low-bit quantization can significantly reduce storage and…
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…
DiffuX2CT: Diffusion Learning to Reconstruct CT Images from Biplanar X-Rays
Xuhui Liu, Zhi Qiao, Runkun Liu +5
Computed tomography (CT) is widely utilized in clinical settings because it delivers detailed 3D images of the human body. However, performing CT scans is not always feasible due t…
DecomCAM: Advancing Beyond Saliency Maps through Decomposition and Integration
Yuguang Yang, Runtang Guo, Sheng Wu +6
Interpreting complex deep networks, notably pre-trained vision-language models (VLMs), is a formidable challenge. Current Class Activation Map (CAM) methods highlight regions revea…
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…