375 citations · 405 across the 17 of their papers we have counts for
10 papers · 1 filter
DiffCLIP: Few-shot Language-driven Multimodal Classifier
Jiaqing Zhang, Mingxiang Cao, Xue Yang +2
Visual language models like Contrastive Language-Image Pretraining (CLIP) have shown impressive performance in analyzing natural images with language information. However, these mo…
Towards Accurate and Efficient Sub-8-Bit Integer Training
Wenjin Guo, Donglai Liu, Weiying Xie +7
Neural network training is a memory- and compute-intensive task. Quantization, which enables low-bitwidth formats in training, can significantly mitigate the workload. To reduce qu…
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…
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…
FoRA: Low-Rank Adaptation Model beyond Multimodal Siamese Network
Weiying Xie, Yusi Zhang, Tianlin Hui +3
Multimodal object detection offers a promising prospect to facilitate robust detection in various visual conditions. However, existing two-stream backbone networks are challenged b…
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…
E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion Detection
Jiaqing Zhang, Mingxiang Cao, Weiying Xie +5
Multimodal image fusion and object detection are crucial for autonomous driving. While current methods have advanced the fusion of texture details and semantic information, their c…
Exploring Hyperspectral Anomaly Detection with Human Vision: A Small Target Aware Detector
Jitao Ma, Weiying Xie, Yunsong Li
Hyperspectral anomaly detection (HAD) aims to localize pixel points whose spectral features differ from the background. HAD is essential in scenarios of unknown or camouflaged targ…
DA-BEV: Unsupervised Domain Adaptation for Bird's Eye View Perception
Kai Jiang, Jiaxing Huang, Weiying Xie +3
Camera-only Bird's Eye View (BEV) has demonstrated great potential in environment perception in a 3D space. However, most existing studies were conducted under a supervised setup w…
Domain Adaptation for Large-Vocabulary Object Detectors
Kai Jiang, Jiaxing Huang, Weiying Xie +4
Large-vocabulary object detectors (LVDs) aim to detect objects of many categories, which learn super objectness features and can locate objects accurately while applied to various…