4 citations · 10 across the 7 of their papers we have counts for
8 papers
CReF: Cross-modal and Recurrent Fusion for Depth-conditioned Humanoid Locomotion
Yuan Hao, Ruiqi Yu, Shixin Luo +3
Stable traversal over geometrically complex terrain increasingly requires exteroceptive perception, yet prior perceptive humanoid locomotion methods often remain tied to explicit g…
DORec: Decomposed Object Reconstruction and Segmentation Utilizing 2D Self-Supervised Features
Jun Wu, Sicheng Li, Sihui Ji +4
Recovering 3D geometry and textures of individual objects is crucial for many robotics applications, such as manipulation, pose estimation, and autonomous driving. However, decompo…
Exploiting Point-Wise Attention in 6D Object Pose Estimation Based on Bidirectional Prediction
Yuhao Yang, Jun Wu, Yue Wang +2
Traditional geometric registration based estimation methods only exploit the CAD model implicitly, which leads to their dependence on observation quality and deficiency to occlusio…
RING++: Roto-translation Invariant Gram for Global Localization on a Sparse Scan Map
Xuecheng Xu, Sha Lu, Jun Wu +5
Global localization plays a critical role in many robot applications. LiDAR-based global localization draws the community's focus with its robustness against illumination and seaso…
Towards Two-view 6D Object Pose Estimation: A Comparative Study on Fusion Strategy
Jun Wu, Lilu Liu, Yue Wang +1
Current RGB-based 6D object pose estimation methods have achieved noticeable performance on datasets and real world applications. However, predicting 6D pose from single 2D image f…
Learning Stereopsis from Geometric Synthesis for 6D Object Pose Estimation
Jun Wu, Lilu Liu, Yue Wang +1
Current monocular-based 6D object pose estimation methods generally achieve less competitive results than RGBD-based methods, mostly due to the lack of 3D information. To make up t…
A Right Invariant Extended Kalman Filter for Object based SLAM
Yang Song, Zhuqing Zhang, Jun Wu +3
With the recent advance of deep learning based object recognition and estimation, it is possible to consider object level SLAM where the pose of each object is estimated in the SLA…
Efficient Learning of Control Policies for Robust Quadruped Bounding using Pretrained Neural Networks
Zhicheng Wang, Anqiao Li, Yixiao Zheng +4
Bounding is one of the important gaits in quadrupedal locomotion for negotiating obstacles. The authors proposed an effective approach that can learn robust bounding gaits more eff…