Haoru Tan,Sitong Wu,Xiuzhe Wu et al.
Haoru Tan et al.
Data plays a pivotal role in the groundbreaking advancements in artificial intelligence. The quantitative analysis of data significantly contributes to model training, enhancing both the efficiency and quality of data utilization. However, ...
Jie Zhang,Shuai Dong,Shiguang Shan et al.
Jie Zhang et al.
Recent approaches employing imperceptible perturbations in input images have demonstrated promising potential to counter malicious manipulations in diffusion-based image editing systems. However, existing methods suffer from limited transfe...
Mayssa Soussia,Gita Ayu Salsabila,Mohamed Ali Mahjoub et al.
Mayssa Soussia et al.
Message passing is a core mechanism in Graph Neural Networks (GNNs), enabling the iterative update of node embeddings by aggregating information from neighboring nodes. Graph Convolutional Networks (GCNs) exemplify this approach by adapting...
ATD: Improved Transformer With Adaptive Token Dictionary for Image Restoration [0.03%]
基于自适应令牌字典的改进型变压器网络用于图像复原
Leheng Zhang,Wei Long,Yawei Li et al.
Leheng Zhang et al.
Recently, Transformers have gained significant popularity in image restoration tasks such as image super-resolution and denoising, owing to their superior performance. However, balancing performance and computational burden remains a long-s...
StructChart: On the Schema, Metric, and Augmentation for Visual Chart Understanding [0.03%]
结构图表：关于视觉图表理解的模式、测度和增强方法
Renqiu Xia,Haoyang Peng,Hancheng Ye et al.
Renqiu Xia et al.
Charts are common in literature across various scientific fields, conveying rich information easily accessible to readers. Current chart-related tasks focus on either chart perception that extracts information from the visual charts, or cha...
Visual-in-Visual: A Unified and Efficient Baseline for Image Restoration [0.03%]
视觉统一基准模型高效地解决图像复原问题
Yuning Cui,Wenqi Ren,Boxin Shi et al.
Yuning Cui et al.
Recent years have witnessed remarkable progress in image restoration, yet achieving both high performance and efficiency remains a persistent challenge. To address this issue, we present VIVNet, a strong and efficient unified baseline desig...
Caixing Wang
Caixing Wang
Random features (RFs) provide an efficient approximation to kernel methods, and allow for scalable learning on large datasets by reducing computational complexity while maintaining strong theoretical guarantees. However, real-world data can...
Flexible-weighted Chamfer Distance: Enhanced Objective Function for Point Cloud Completion [0.03%]
柔性加权奇弗距离：点云补全的增强型目标函数
Jie Li,Shengwei Tian,Long Yu et al.
Jie Li et al.
The Chamfer Distance (CD) is a cornerstone objective function for point cloud completion, yet its inherent symmetric weighting mechanism limits the quality of the generated results. By penalizing local detail deviations and global coverage ...
AIRPNet: Adaptive Image Restoration With Privacy Protection in Steganographic Domain [0.03%]
具有隐私保护的隐写领域自适应图像修复方法(AIRPNet)
Fangyuan Gao,Chao Gao,Xin Deng et al.
Fangyuan Gao et al.
Cloud-based third-party multimedia services have become increasingly popular in last decade, however, they pose serious threats to users' privacy. To address this issue, in this paper, we propose a novel Adaptive Image Restoration network w...
Chongzhen Tian,Zhengxin Li,Hui Yuan et al.
Chongzhen Tian et al.
Machine vision systems, which can efficiently manage extensive visual perception tasks, are becoming increasingly popular in industrial production and daily life. Due to the challenge of simultaneously obtaining accurate depth and texture i...