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20162023
most citedImage Inpainting by End-to-End Cascaded Refinement with Mask Awareness

140 citations · 919 across the 60 of their papers we have counts for

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Showing 2018 · cs.CVShow all

6 papers · 2 filters

cs.CV2018★ 12 cited

Spectral Feature Transformation for Person Re-identification

Chuanchen Luo, Yuntao Chen, Naiyan Wang +1

With the surge of deep learning techniques, the field of person re-identification has witnessed rapid progress in recent years. Deep learning based methods focus on learning a feat…

cs.CV2018★ 20 cited

CIAN: Cross-Image Affinity Net for Weakly Supervised Semantic Segmentation

Junsong Fan, Zhaoxiang Zhang, Tieniu Tan +2

Weakly supervised semantic segmentation with only image-level labels saves large human effort to annotate pixel-level labels. Cutting-edge approaches rely on various innovative con…

cs.CV2018★ 8 cited

Accelerating Deep Neural Networks with Spatial Bottleneck Modules

Junran Peng, Lingxi Xie, Zhaoxiang Zhang +2

This paper presents an efficient module named spatial bottleneck for accelerating the convolutional layers in deep neural networks. The core idea is to decompose convolution into t…

cs.CV2018

Hard-Aware Point-to-Set Deep Metric for Person Re-identification

Rui Yu, Zhiyong Dou, Song Bai +3

Person re-identification (re-ID) is a highly challenging task due to large variations of pose, viewpoint, illumination, and occlusion. Deep metric learning provides a satisfactory…

cs.CV2018★ 14 cited

Relational Network for Skeleton-Based Action Recognition

Wu Zheng, Lin Li, Zhaoxiang Zhang +2

With the fast development of effective and low-cost human skeleton capture systems, skeleton-based action recognition has attracted much attention recently. Most existing methods u…

cs.CV2018★ 112 cited

Multi-pseudo Regularized Label for Generated Data in Person Re-Identification

Yan Huang, Jinsong Xu, Qiang Wu +3

Sufficient training data normally is required to train deeply learned models. However, due to the expensive manual process for labelling large number of images, the amount of avail…