activity
20182021
most citedAdaSample: Adaptive Sampling of Hard Positives for Descriptor Learning

6 citations · 12 across the 5 of their papers we have counts for

collaborators

14 papers

cs.CV2021

Free Lunch for Co-Saliency Detection: Context Adjustment

Lingdong Kong, Prakhar Ganesh, Tan Wang +3

We unveil a long-standing problem in the prevailing co-saliency detection systems: there is indeed inconsistency between training and testing. Constructing a high-quality co-salien…

cs.CV20204 cited

Generalized Zero-Shot Learning via VAE-Conditioned Generative Flow

Yu-Chao Gu, Le Zhang, Yun Liu +2

Generalized zero-shot learning (GZSL) aims to recognize both seen and unseen classes by transferring knowledge from semantic descriptions to visual representations. Recent generati…

cs.CV2020

Regularized Densely-connected Pyramid Network for Salient Instance Segmentation

Yu-Huan Wu, Yun Liu, Le Zhang +2

Much of the recent efforts on salient object detection (SOD) have been devoted to producing accurate saliency maps without being aware of their instance labels. To this end, we pro…

cs.CV2020

Disentangling Human Error from the Ground Truth in Segmentation of Medical Images

Le Zhang, Ryutaro Tanno, Mou-Cheng Xu +5

Recent years have seen increasing use of supervised learning methods for segmentation tasks. However, the predictive performance of these algorithms depends on the quality of label…

cs.CV20196 cited

AdaSample: Adaptive Sampling of Hard Positives for Descriptor Learning

Xin-Yu Zhang, Le Zhang, Zao-Yi Zheng +3

Triplet loss has been widely employed in a wide range of computer vision tasks, including local descriptor learning. The effectiveness of the triplet loss heavily relies on the tri…

cs.CV2019

Robust Regression via Deep Negative Correlation Learning

Le Zhang, Zenglin Shi, Ming-Ming Cheng +5

Nonlinear regression has been extensively employed in many computer vision problems (e.g., crowd counting, age estimation, affective computing). Under the umbrella of deep learning…