8 citations · 20 across the 39 of their papers we have counts for
9 papers · 2 filters
P-SAM: SAM with Perceptual Parallel Prompt for Few-Shot Strip Steel Surface Defect Segmentation
Qian Xu, Hang Xiong, Anpeng Wang +3
Few-shot semantic segmentation (FSS) of strip steel surface defects (SD) has posed significant challenges distinct from natural scenes. Unlike natural images, SD task exhib…
SphereSOD: Geometry-Structure Coupled Learning for 360 Salient Object Detection
Junsong Zhang, Zhijie Shen, Shuai Zheng +4
360° salient object detection (SOD) aims to accurately segment salient regions across a full field of view. However, equirectangular projection (ERP) introduces severe spatial dist…
ICME 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for High-Precision Manufacturing
Wei Sun, Weixia Zhang, Linhan Cao +30
This paper presents the IEEE International Conference on Multimedia and Expo (ICME) 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for Hi…
M-SAM: Multi-Modal Mixture-of-Experts with Memory-Augmented SAM for RGB-D Video Salient Object Detection
Jiyuan Liu, Jia Lin, Xiaofei Zhou +3
The Segment Anything Model 2 (SAM2) has emerged as a foundation model for universal segmentation. Owing to its generalizable visual representations, SAM2 has been successfully appl…
G2HFNet: GeoGran-Aware Hierarchical Feature Fusion Network for Salient Object Detection in Optical Remote Sensing Images
Bin Wan, Runmin Cong, Xiaofei Zhou +3
Remote sensing images captured from aerial perspectives often exhibit significant scale variations and complex backgrounds, posing challenges for salient object detection (SOD). Ex…
RSONet: Region-guided Selective Optimization Network for RGB-T Salient Object Detection
Bin Wan, Runmin Cong, Xiaofei Zhou +3
This paper focuses on the inconsistency in salient regions between RGB and thermal images. To address this issue, we propose the Region-guided Selective Optimization Network for RG…
Mastering Negation: Boosting Grounding Models via Grouped Opposition-Based Learning
Zesheng Yang, Xi Jiang, Bingzhang Hu +4
Current vision-language detection and grounding models predominantly focus on prompts with positive semantics and often struggle to accurately interpret and ground complex expressi…
RDNet: Region Proportion-Aware Dynamic Adaptive Salient Object Detection Network in Optical Remote Sensing Images
Bin Wan, Runmin Cong, Xiaofei Zhou +3
Salient object detection (SOD) in remote sensing images faces significant challenges due to large variations in object sizes, the computational cost of self-attention mechanisms, a…
Taming Real-World Space-Time Video Super-Resolution with One-Step Diffusion
Shuoyan Wei, Feng Li, Chen Zhou +3
Diffusion models have demonstrated exceptional success in video super-resolution (VSR), exhibiting powerful capabilities for generating fine-grained details. However, their potenti…