6 papers
Towards Real Zero-Shot Camouflaged Object Segmentation without Camouflaged Annotations
Cheng Lei, Jie Fan, Xinran Li +4
Camouflaged Object Segmentation (COS) faces significant challenges due to the scarcity of annotated data, where meticulous pixel-level annotation is both labor-intensive and costly…
Deep Learning Empowered Super-Resolution: A Comprehensive Survey and Future Prospects
Le Zhang, Ao Li, Qibin Hou +2
Super-resolution (SR) has garnered significant attention within the computer vision community, driven by advances in deep learning (DL) techniques and the growing demand for high-q…
MobileIE: An Extremely Lightweight and Effective ConvNet for Real-Time Image Enhancement on Mobile Devices
Hailong Yan, Ao Li, Xiangtao Zhang +4
Recent advancements in deep neural networks have driven significant progress in image enhancement (IE). However, deploying deep learning models on resource-constrained platforms, s…
WiFi CSI Based Temporal Activity Detection via Dual Pyramid Network
Zhendong Liu, Le Zhang, Bing Li +3
We address the challenge of WiFi-based temporal activity detection and propose an efficient Dual Pyramid Network that integrates Temporal Signal Semantic Encoders and Local Sensiti…
From Dense to Sparse: Event Response for Enhanced Residential Load Forecasting
Xin Cao, Qinghua Tao, Yingjie Zhou +5
Residential load forecasting (RLF) is crucial for resource scheduling in power systems. Most existing methods utilize all given load records (dense data) to indiscriminately extrac…
Towards Open-Vocabulary Video Semantic Segmentation
Xinhao Li, Yun Liu, Guolei Sun +3
Semantic segmentation in videos has been a focal point of recent research. However, existing models encounter challenges when faced with unfamiliar categories. To address this, we…