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20212024
most citedUnleashing the Power of Generic Segmentation Models: A Simple Baseline for Infrared Small Target Detection

28 citations · 40 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV202428 cited

Unleashing the Power of Generic Segmentation Models: A Simple Baseline for Infrared Small Target Detection

Mingjin Zhang, Chi Zhang, Qiming Zhang +3

Recent advancements in deep learning have greatly advanced the field of infrared small object detection (IRSTD). Despite their remarkable success, a notable gap persists between th…

cs.DC2024

FedFQ: Federated Learning with Fine-Grained Quantization

Haowei Li, Weiying Xie, Hangyu Ye +3

Federated learning (FL) is a decentralized approach, enabling multiple participants to collaboratively train a model while ensuring the protection of data privacy. The transmission…

cs.CV2024

Reducing Spurious Correlation for Federated Domain Generalization

Shuran Ma, Weiying Xie, Daixun Li +2

The rapid development of multimedia has provided a large amount of data with different distributions for visual tasks, forming different domains. Federated Learning (FL) can effici…

cs.MM2024

Beyond Alignment: Blind Video Face Restoration via Parsing-Guided Temporal-Coherent Transformer

Kepeng Xu, Li Xu, Gang He +2

Multiple complex degradations are coupled in low-quality video faces in the real world. Therefore, blind video face restoration is a highly challenging ill-posed problem, requiring…

cs.CV20241 cited

Hyperspectral Anomaly Detection with Self-Supervised Anomaly Prior

Yidan Liu, Weiying Xie, Kai Jiang +3

The majority of existing hyperspectral anomaly detection (HAD) methods use the low-rank representation (LRR) model to separate the background and anomaly components, where the anom…

cs.CV20241 cited

Multimodal Informative ViT: Information Aggregation and Distribution for Hyperspectral and LiDAR Classification

Jiaqing Zhang, Jie Lei, Weiying Xie +3

In multimodal land cover classification (MLCC), a common challenge is the redundancy in data distribution, where irrelevant information from multiple modalities can hinder the effe…