14 citations · 18 across the 9 of their papers we have counts for
7 papers · 1 filter
Semantic Localization Guiding Segment Anything Model For Reference Remote Sensing Image Segmentation
Shuyang Li, Shuang Wang, Zhuangzhuang Sun +1
The Reference Remote Sensing Image Segmentation (RRSIS) task generates segmentation masks for specified objects in images based on textual descriptions, which has attracted widespr…
EventVAD: Training-Free Event-Aware Video Anomaly Detection
Yihua Shao, Haojin He, Sijie Li +11
Video Anomaly Detection~(VAD) focuses on identifying anomalies within videos. Supervised methods require an amount of in-domain training data and often struggle to generalize to un…
XIMAGENET-12: An Explainable AI Benchmark Dataset for Model Robustness Evaluation
Qiang Li, Dan Zhang, Shengzhao Lei +5
Despite the promising performance of existing visual models on public benchmarks, the critical assessment of their robustness for real-world applications remains an ongoing challen…
SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation
Zhuoyan Luo, Yicheng Xiao, Yong Liu +5
This paper studies referring video object segmentation (RVOS) by boosting video-level visual-linguistic alignment. Recent approaches model the RVOS task as a sequence prediction pr…
Towards Realizing the Value of Labeled Target Samples: a Two-Stage Approach for Semi-Supervised Domain Adaptation
mengqun Jin, Kai Li, Shuyan Li +2
Semi-Supervised Domain Adaptation (SSDA) is a recently emerging research topic that extends from the widely-investigated Unsupervised Domain Adaptation (UDA) by further having a fe…
SSGD: A smartphone screen glass dataset for defect detection
Haonan Han, Rui Yang, Shuyan Li +2
Interactive devices with touch screen have become commonly used in various aspects of daily life, which raises the demand for high production quality of touch screen glass. While i…
Adversarial Alignment for Source Free Object Detection
Qiaosong Chu, Shuyan Li, Guangyi Chen +2
Source-free object detection (SFOD) aims to transfer a detector pre-trained on a label-rich source domain to an unlabeled target domain without seeing source data. While most exist…