290 citations · 424 across the 25 of their papers we have counts for
11 papers · 1 filter
PolSAM: Polarimetric Scattering Mechanism Informed Segment Anything Model
Yuqing Wang, Zhongling Huang, Shuxin Yang +4
PolSAR data presents unique challenges due to its rich and complex characteristics. Existing data representations, such as complex-valued data, polarimetric features, and amplitude…
DGTR: Distributed Gaussian Turbo-Reconstruction for Sparse-View Vast Scenes
Hao Li, Yuanyuan Gao, Haosong Peng +7
Novel-view synthesis (NVS) approaches play a critical role in vast scene reconstruction. However, these methods rely heavily on dense image inputs and prolonged training times, mak…
Mamba Capsule Routing Towards Part-Whole Relational Camouflaged Object Detection
Dingwen Zhang, Liangbo Cheng, Yi Liu +2
The part-whole relational property endowed by Capsule Networks (CapsNets) has been known successful for camouflaged object detection due to its segmentation integrity. However, the…
Retinex-RAWMamba: Bridging Demosaicing and Denoising for Low-Light RAW Image Enhancement
Xianmin Chen, Longfei Han, Peiliang Huang +3
Low-light image enhancement, particularly in cross-domain tasks such as mapping from the raw domain to the sRGB domain, remains a significant challenge. Many deep learning-based me…
ASPS: Augmented Segment Anything Model for Polyp Segmentation
Huiqian Li, Dingwen Zhang, Jieru Yao +3
Polyp segmentation plays a pivotal role in colorectal cancer diagnosis. Recently, the emergence of the Segment Anything Model (SAM) has introduced unprecedented potential for polyp…
VDG: Vision-Only Dynamic Gaussian for Driving Simulation
Hao Li, Jingfeng Li, Dingwen Zhang +7
Dynamic Gaussian splatting has led to impressive scene reconstruction and image synthesis advances in novel views. Existing methods, however, heavily rely on pre-computed poses and…
Center-Sensitive Kernel Optimization for Efficient On-Device Incremental Learning
Dingwen Zhang, Yan Li, De Cheng +2
To facilitate the evolution of edge intelligence in ever-changing environments, we study on-device incremental learning constrained in limited computation resource in this paper. C…
Boosting Medical Image-based Cancer Detection via Text-guided Supervision from Reports
Guangyu Guo, Jiawen Yao, Yingda Xia +7
The absence of adequately sufficient expert-level tumor annotations hinders the effectiveness of supervised learning based opportunistic cancer screening on medical imaging. Clinic…
Unsupervised Pre-training with Language-Vision Prompts for Low-Data Instance Segmentation
Dingwen Zhang, Hao Li, Diqi He +4
In recent times, following the paradigm of DETR (DEtection TRansformer), query-based end-to-end instance segmentation (QEIS) methods have exhibited superior performance compared to…
GGRt: Towards Pose-free Generalizable 3D Gaussian Splatting in Real-time
Hao Li, Yuanyuan Gao, Chenming Wu +7
This paper presents GGRt, a novel approach to generalizable novel view synthesis that alleviates the need for real camera poses, complexity in processing high-resolution images, an…
Continual All-in-One Adverse Weather Removal with Knowledge Replay on a Unified Network Structure
De Cheng, Yanling Ji, Dong Gong +4
In real-world applications, image degeneration caused by adverse weather is always complex and changes with different weather conditions from days and seasons. Systems in real-worl…