CRIN: Rotation-Invariant Point Cloud Analysis and Rotation Estimation via Centrifugal Reference Frame

1 code implementation • 6 Mar 2023 • Yujing Lou, Zelin Ye, Yang You, Nianjuan Jiang, Jiangbo Lu, Weiming Wang, Lizhuang Ma, Cewu Lu

CRIN directly takes the coordinates of points as input and transforms local points into rotation-invariant representations via centrifugal reference frames.

Understanding Pixel-level 2D Image Semantics with 3D Keypoint Knowledge Engine

no code implementations • 21 Nov 2021 • Yang You, Chengkun Li, Yujing Lou, Zhoujun Cheng, Liangwei Li, Lizhuang Ma, Weiming Wang, Cewu Lu

Pixel-level 2D object semantic understanding is an important topic in computer vision and could help machine deeply understand objects (e. g. functionality and affordance) in our daily life.

Localization with Sampling-Argmax

1 code implementation • NeurIPS 2021 • Jiefeng Li, Tong Chen, Ruiqi Shi, Yujing Lou, Yong-Lu Li, Cewu Lu

In this work, we propose sampling-argmax, a differentiable training method that imposes implicit constraints to the shape of the probability map by minimizing the expectation of the localization error.

3D Human Pose Estimation

PRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features

2 code implementations • 24 Feb 2021 • Yang You, Yujing Lou, Ruoxi Shi, Qi Liu, Yu-Wing Tai, Lizhuang Ma, Weiming Wang, Cewu Lu

Spherical Voxel Convolution and Point Re-sampling are proposed to extract rotation invariant features for each point.

3D Feature Matching Data Augmentation

Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes

1 code implementation • CVPR 2022 • Yang You, Zelin Ye, Yujing Lou, Chengkun Li, Yong-Lu Li, Lizhuang Ma, Weiming Wang, Cewu Lu

In the work, we disentangle the direct offset into Local Canonical Coordinates (LCC), box scales and box orientations.

3D Object Detection object-detection

Semantic Correspondence via 2D-3D-2D Cycle

1 code implementation • 20 Apr 2020 • Yang You, Chengkun Li, Yujing Lou, Zhoujun Cheng, Lizhuang Ma, Cewu Lu, Weiming Wang

Visual semantic correspondence is an important topic in computer vision and could help machine understand objects in our daily life.

Semantic correspondence

KeypointNet: A Large-scale 3D Keypoint Dataset Aggregated from Numerous Human Annotations

1 code implementation • CVPR 2020 • Yang You, Yujing Lou, Chengkun Li, Zhoujun Cheng, Liangwei Li, Lizhuang Ma, Weiming Wang, Cewu Lu

Detecting 3D objects keypoints is of great interest to the areas of both graphics and computer vision.

Human Correspondence Consensus for 3D Object Semantic Understanding

1 code implementation • ECCV 2020 • Yujing Lou, Yang You, Chengkun Li, Zhoujun Cheng, Liangwei Li, Lizhuang Ma, Weiming Wang, Cewu Lu

Semantic understanding of 3D objects is crucial in many applications such as object manipulation.

3D Feature Matching 3D Point Cloud Matching +1

Pointwise Rotation-Invariant Network with Adaptive Sampling and 3D Spherical Voxel Convolution

1 code implementation • 23 Nov 2018 • Yang You, Yujing Lou, Qi Liu, Yu-Wing Tai, Lizhuang Ma, Cewu Lu, Weiming Wang

Point cloud analysis without pose priors is very challenging in real applications, as the orientations of point clouds are often unknown.

3D Feature Matching Data Augmentation