1 citations · 1 across the 4 of their papers we have counts for
4 papers
CLAR: Learning 3D Representations for Robotic Manipulation by Fusing Masked Reconstruction with Multi-Level Contrastive Alignment
Wenbo Cui, Chengyang Zhao, Yuhui Chen +4
The spatial information inherent in 3D point clouds is crucial for robotic manipulation. However, existing 3D pre-training methods face a fundamental trade-off: Masked Autoencoding…
RoboVerse: Towards a Unified Platform, Dataset and Benchmark for Scalable and Generalizable Robot Learning
Haoran Geng, Feishi Wang, Songlin Wei +34
Data scaling and standardized evaluation benchmarks have driven significant advances in natural language processing and computer vision. However, robotics faces unique challenges i…
GAPartManip: A Large-scale Part-centric Dataset for Material-Agnostic Articulated Object Manipulation
Wenbo Cui, Chengyang Zhao, Songlin Wei +5
Effectively manipulating articulated objects in household scenarios is a crucial step toward achieving general embodied artificial intelligence. Mainstream research in 3D vision ha…
D3RoMa: Disparity Diffusion-based Depth Sensing for Material-Agnostic Robotic Manipulation
Songlin Wei, Haoran Geng, Jiayi Chen +6
Depth sensing is an important problem for 3D vision-based robotics. Yet, a real-world active stereo or ToF depth camera often produces noisy and incomplete depth which bottlenecks…