5 papers
Localization with Sampling-Argmax
Jiefeng Li, Tong Chen, Ruiqi Shi +3
Soft-argmax operation is commonly adopted in detection-based methods to localize the target position in a differentiable manner. However, training the neural network with soft-argm…
Semantic Correspondence via 2D-3D-2D Cycle
Yang You, Chengkun Li, Yujing Lou +4
Visual semantic correspondence is an important topic in computer vision and could help machine understand objects in our daily life. However, most previous methods directly train o…
KeypointNet: A Large-scale 3D Keypoint Dataset Aggregated from Numerous Human Annotations
Yang You, Yujing Lou, Chengkun Li +5
Detecting 3D objects keypoints is of great interest to the areas of both graphics and computer vision. There have been several 2D and 3D keypoint datasets aiming to address this pr…
Human Correspondence Consensus for 3D Object Semantic Understanding
Yujing Lou, Yang You, Chengkun Li +5
Semantic understanding of 3D objects is crucial in many applications such as object manipulation. However, it is hard to give a universal definition of point-level semantics that e…
Pointwise Rotation-Invariant Network with Adaptive Sampling and 3D Spherical Voxel Convolution
Yang You, Yujing Lou, Qi Liu +4
Point cloud analysis without pose priors is very challenging in real applications, as the orientations of point clouds are often unknown. In this paper, we propose a brand new poin…