123 citations · 182 across the 6 of their papers we have counts for
6 papers
Expansion and Shrinkage of Localization for Weakly-Supervised Semantic Segmentation
Jinlong Li, Zequn Jie, Xu Wang +2
Generating precise class-aware pseudo ground-truths, a.k.a, class activation maps (CAMs), is essential for weakly-supervised semantic segmentation. The original CAM method usually…
Predictive and Contrastive: Dual-Auxiliary Learning for Recommendation
Yinghui Tao, Min Gao, Junliang Yu +3
Self-supervised learning (SSL) recently has achieved outstanding success on recommendation. By setting up an auxiliary task (either predictive or contrastive), SSL can discover sup…
Robust and Precise Facial Landmark Detection by Self-Calibrated Pose Attention Network
Jun Wan, Hui Xi, Jie Zhou +4
Current fully-supervised facial landmark detection methods have progressed rapidly and achieved remarkable performance. However, they still suffer when coping with faces under larg…
A Feature Consistency Driven Attention Erasing Network for Fine-Grained Image Retrieval
Qi Zhao, Xu Wang, Shuchang Lyu +2
Large-scale fine-grained image retrieval has two main problems. First, low dimensional feature embedding can fasten the retrieval process but bring accuracy reduce due to overlooki…
TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarios
Xingkui Zhu, Shuchang Lyu, Xu Wang +1
Object detection on drone-captured scenarios is a recent popular task. As drones always navigate in different altitudes, the object scale varies violently, which burdens the optimi…
A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation
Qi Zhao, Binghao Liu, Shuchang Lyu +1
Few-shot segmentation focuses on the generalization of models to segment unseen object with limited annotated samples. However, existing approaches still face two main challenges.…