1.4k citations · 3.6k across the 125 of their papers we have counts for
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PGNet: Pose-Guided Point Cloud Generating Networks for 6-DoF Object Pose Estimation
Peiyu Yu, Yongming Rao, Jiwen Lu +1
Humans are able to perform fast and accurate object pose estimation even under severe occlusion by exploiting learned object model priors from everyday life. However, most recently…
Automatic Data Augmentation by Learning the Deterministic Policy
Yinghuan Shi, Tiexin Qin, Yong Liu +3
Aiming to produce sufficient and diverse training samples, data augmentation has been demonstrated for its effectiveness in training deep models. Regarding that the criterion of th…
DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing
Yongcheng Liu, Bin Fan, Gaofeng Meng +3
Point cloud processing is very challenging, as the diverse shapes formed by irregular points are often indistinguishable. A thorough grasp of the elusive shape requires sufficientl…
Conditional Single-view Shape Generation for Multi-view Stereo Reconstruction
Yi Wei, Shaohui Liu, Wang Zhao +2
In this paper, we present a new perspective towards image-based shape generation. Most existing deep learning based shape reconstruction methods employ a single-view deterministic…
BridgeNet: A Continuity-Aware Probabilistic Network for Age Estimation
Wanhua Li, Jiwen Lu, Jianjiang Feng +3
Age estimation is an important yet very challenging problem in computer vision. Existing methods for age estimation usually apply a divide-and-conquer strategy to deal with heterog…
Deep Fitting Degree Scoring Network for Monocular 3D Object Detection
Lijie Liu, Jiwen Lu, Chunjing Xu +2
In this paper, we propose to learn a deep fitting degree scoring network for monocular 3D object detection, which aims to score fitting degree between proposals and object conclusi…
COIN: A Large-scale Dataset for Comprehensive Instructional Video Analysis
Yansong Tang, Dajun Ding, Yongming Rao +5
There are substantial instructional videos on the Internet, which enables us to acquire knowledge for completing various tasks. However, most existing datasets for instructional vi…
Hardness-Aware Deep Metric Learning
Wenzhao Zheng, Zhaodong Chen, Jiwen Lu +1
This paper presents a hardness-aware deep metric learning (HDML) framework. Most previous deep metric learning methods employ the hard negative mining strategy to alleviate the lac…