234 citations · 291 across the 12 of their papers we have counts for
12 papers
CTFS : Collaborative Teacher Framework for Forward-Looking Sonar Image Semantic Segmentation with Extremely Limited Labels
Ping Guo, Chengzhou Li, Guanchen Meng +6
As one of the most important underwater sensing technologies, forward-looking sonar exhibits unique imaging characteristics. Sonar images are often affected by severe speckle noise…
RSOD: Reliability-Guided Sonar Image Object Detection with Extremely Limited Labels
Chengzhou Li, Ping Guo, Guanchen Meng +7
Object detection in sonar images is a key technology in underwater detection systems. Compared to natural images, sonar images contain fewer texture details and are more susceptibl…
Motion-Driven Neural Optimizer for Prophylactic Braces Made by Distributed Microstructures
Xingjian Han, Yu Jiang, Weiming Wang +9
Joint injuries, and their long-term consequences, present a substantial global health burden. Wearable prophylactic braces are an attractive potential solution to reduce the incide…
Learning Heavily-Degraded Prior for Underwater Object Detection
Chenping Fu, Xin Fan, Jiewen Xiao +3
Underwater object detection suffers from low detection performance because the distance and wavelength dependent imaging process yield evident image quality degradations such as ha…
Bilevel Generative Learning for Low-Light Vision
Yingchi Liu, Zhu Liu, Long Ma +4
Recently, there has been a growing interest in constructing deep learning schemes for Low-Light Vision (LLV). Existing techniques primarily focus on designing task-specific and dat…
Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation
Jinyuan Liu, Zhu Liu, Guanyao Wu +5
Multi-modality image fusion and segmentation play a vital role in autonomous driving and robotic operation. Early efforts focus on boosting the performance for only one task, \emph…
DPM-OT: A New Diffusion Probabilistic Model Based on Optimal Transport
Zezeng Li, ShengHao Li, Zhanpeng Wang +3
Sampling from diffusion probabilistic models (DPMs) can be viewed as a piecewise distribution transformation, which generally requires hundreds or thousands of steps of the inverse…
OT-Net: A Reusable Neural Optimal Transport Solver
Zezeng Li, Shenghao Li, Lianbao Jin +2
With the widespread application of optimal transport (OT), its calculation becomes essential, and various algorithms have emerged. However, the existing methods either have low eff…
A Task-guided, Implicitly-searched and Meta-initialized Deep Model for Image Fusion
Risheng Liu, Zhu Liu, Jinyuan Liu +2
Image fusion plays a key role in a variety of multi-sensor-based vision systems, especially for enhancing visual quality and/or extracting aggregated features for perception. Howev…
Practical exposure correction via compensation
Long Ma, Nan An, Jinyuan Liu +4
In computer vision, correcting the exposure level is a fundamental task for enhancing the visual quality of observations with inappropriate lightness. However, existing methodologi…
CoCoNet: Coupled Contrastive Learning Network with Multi-level Feature Ensemble for Multi-modality Image Fusion
Jinyuan Liu, Runjia Lin, Guanyao Wu +3
Infrared and visible image fusion targets to provide an informative image by combining complementary information from different sensors. Existing learning-based fusion approaches a…
Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection
Jinyuan Liu, Xin Fan, Zhanbo Huang +4
This study addresses the issue of fusing infrared and visible images that appear differently for object detection. Aiming at generating an image of high visual quality, previous ap…