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20222026
most citedLearning Non-target Knowledge for Few-shot Semantic Segmentation

6 citations · 12 across the 16 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.CV2023

Domain Prompt Learning with Quaternion Networks

Qinglong Cao, Zhengqin Xu, Yuntian Chen +2

Prompt learning has emerged as an effective and data-efficient technique in large Vision-Language Models (VLMs). However, when adapting VLMs to specialized domains such as remote s…

cs.LG2023

CLeaRForecast: Contrastive Learning of High-Purity Representations for Time Series Forecasting

Jiaxin Gao, Yuxiao Hu, Qinglong Cao +2

Time series forecasting (TSF) holds significant importance in modern society, spanning numerous domains. Previous representation learning-based TSF algorithms typically embrace a c…

eess.SP2023

MoE-AMC: Enhancing Automatic Modulation Classification Performance Using Mixture-of-Experts

Jiaxin Gao, Qinglong Cao, Yuntian Chen

Automatic Modulation Classification (AMC) plays a vital role in time series analysis, such as signal classification and identification within wireless communications. Deep learning…

cs.CV2023

Domain-Controlled Prompt Learning

Qinglong Cao, Zhengqin Xu, Yuntian Chen +2

Large pre-trained vision-language models, such as CLIP, have shown remarkable generalization capabilities across various tasks when appropriate text prompts are provided. However,…

cs.CV2023

Reflection Invariance Learning for Few-shot Semantic Segmentation

Qinglong Cao, Yuntian Chen, Chao Ma +1

Few-shot semantic segmentation (FSS) aims to segment objects of unseen classes in query images with only a few annotated support images. Existing FSS algorithms typically focus on…

cs.CV2023

Few-Shot Rotation-Invariant Aerial Image Semantic Segmentation

Qinglong Cao, Yuntian Chen, Chao Ma +1

Few-shot aerial image segmentation is a challenging task that involves precisely parsing objects in query aerial images with limited annotated support. Conventional matching method…