158 citations · 351 across the 16 of their papers we have counts for
24 papers · 1 filter
Thunder: Thumbnail based Fast Lightweight Image Denoising Network
Yifeng Zhou, Xing Xu, Shuaicheng Liu +3
To achieve promising results on removing noise from real-world images, most of existing denoising networks are formulated with complex network structure, making them impractical fo…
Relation Regularized Scene Graph Generation
Yuyu Guo, Lianli Gao, Jingkuan Song +4
Scene graph generation (SGG) is built on top of detected objects to predict object pairwise visual relations for describing the image content abstraction. Existing works have revea…
From General to Specific: Informative Scene Graph Generation via Balance Adjustment
Yuyu Guo, Lianli Gao, Xuanhan Wang +5
The scene graph generation (SGG) task aims to detect visual relationship triplets, i.e., subject, predicate, object, in an image, providing a structural vision layout for scene und…
Webly Supervised Fine-Grained Recognition: Benchmark Datasets and An Approach
Zeren Sun, Yazhou Yao, Xiu-Shen Wei +5
Learning from the web can ease the extreme dependence of deep learning on large-scale manually labeled datasets. Especially for fine-grained recognition, which targets at distingui…
Patch-wise++ Perturbation for Adversarial Targeted Attacks
Lianli Gao, Qilong Zhang, Jingkuan Song +1
Although great progress has been made on adversarial attacks for deep neural networks (DNNs), their transferability is still unsatisfactory, especially for targeted attacks. There…
Dual ResGCN for Balanced Scene GraphGeneration
Jingyi Zhang, Yong Zhang, Baoyuan Wu +3
Visual scene graph generation is a challenging task. Previous works have achieved great progress, but most of them do not explicitly consider the class imbalance issue in scene gra…