MB-RACS: Measurement-Bounds-based Rate-Adaptive Image Compressed Sensing Network [0.03%]
基于测量边界自适应率的图像压缩感知网络
Yujun Huang,Bin Chen,Naiqi Li et al.
Yujun Huang et al.
Conventional compressed sensing (CS) algorithms typically apply a uniform sampling rate to different image blocks. A more strategic approach could be to allocate the number of measurements adaptively, based on each image block's complexity....
Hafsa Ennajari,Nizar Bouguila,Jamal Bentahar
Hafsa Ennajari
With the prevalence of short texts in various forms such as news headlines, tweets, and reviews, short text analysis has gained significant interest in recent times. However, modeling short texts remains a challenging task due to its sparse...
Zhi Hou,Baosheng Yu,Chaoyue Wang et al.
Zhi Hou et al.
Despite the great success achieved, deep learning technologies usually suffer from data scarcity issues in real-world applications, where existing methods mainly explore sample relationships in a vanilla way from the perspectives of either ...
Monte Carlo Neural PDE Solver for Learning PDEs Via Probabilistic Representation [0.03%]
基于概率表示学习PDE的蒙特卡罗神经PDE求解器
Rui Zhang,Qi Meng,Rongchan Zhu et al.
Rui Zhang et al.
In scenarios with limited available data, training the function-to-function neural PDE solver in an unsupervised manner is essential. However, the efficiency and accuracy of existing methods are constrained by the properties of numerical al...
Jingchun Zhou,Zongxin He,Dehuan Zhang et al.
Jingchun Zhou et al.
Feature drift is caused by the dynamic coupling of target features and degradation factors, which reduce underwater detector performance. We redefine feature drift as the instability of target features within boundary constraints while solv...
A Lightweight Deep Exclusion Unfolding Network for Single Image Reflection Removal [0.03%]
单反光移除的轻量级深度排除展开网络
Jun-Jie Huang,Tianrui Liu,Zihan Chen et al.
Jun-Jie Huang et al.
Single Image Reflection Removal (SIRR) is a canonical blind source separation problem and refers to the issue of separating a reflection-contaminated image into a transmission and a reflection image. The core challenge lies in minimizing th...
Jiawei Liu,Cheng Yang,Zhiyuan Lu et al.
Jiawei Liu et al.
Foundation models have emerged as critical components in a variety of artificial intelligence applications, and showcase significant success in natural language processing and several other domains. Meanwhile, the field of graph machine lea...
MAIR++: Improving Multi-view Attention Inverse Rendering with Implicit Lighting Representation [0.03%]
MAIR++: 利用隐式光照表征提升多视角注意力逆向渲染技术
JunYong Choi,SeokYeong Lee,Haesol Park et al.
JunYong Choi et al.
In this paper, we propose a scene-level inverse rendering framework that uses multi-view images to decompose the scene into geometry, SVBRDF, and 3D spatially-varying lighting. While multi-view images have been widely used for object-level ...
Visible-Thermal Tiny Object Detection: A Benchmark Dataset and Baselines [0.03%]
可见光-红外小物体检测：数据集和基准方法研究
Xinyi Ying,Chao Xiao,Wei An et al.
Xinyi Ying et al.
Visible-thermal small object detection (RGBT SOD) is a significant yet challenging task with a wide range of applications, including video surveillance, traffic monitoring, search and rescue. However, existing studies mainly focus on either...
Alon Harell,Yalda Foroutan,Nilesh Ahuja et al.
Alon Harell et al.
Recent years have seen a tremendous growth in both the capability and popularity of automatic machine analysis of media, especially images and video. As a result, a growing need for efficient compression methods optimised for machine vision...