66 citations · 216 across the 50 of their papers we have counts for
11 papers · 1 filter
TexPose: Neural Texture Learning for Self-Supervised 6D Object Pose Estimation
Hanzhi Chen, Fabian Manhardt, Nassir Navab +1
In this paper, we introduce neural texture learning for 6D object pose estimation from synthetic data and a few unlabelled real images. Our major contribution is a novel learning s…
HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios
HyunJun Jung, Guangyao Zhai, Shun-Cheng Wu +10
Estimating 6D object poses is a major challenge in 3D computer vision. Building on successful instance-level approaches, research is shifting towards category-level pose estimation…
MonoGraspNet: 6-DoF Grasping with a Single RGB Image
Guangyao Zhai, Dianye Huang, Shun-Cheng Wu +6
6-DoF robotic grasping is a long-lasting but unsolved problem. Recent methods utilize strong 3D networks to extract geometric grasping representations from depth sensors, demonstra…
Segmenting Known Objects and Unseen Unknowns without Prior Knowledge
Stefano Gasperini, Alvaro Marcos-Ramiro, Michael Schmidt +3
Panoptic segmentation methods assign a known class to each pixel given in input. Even for state-of-the-art approaches, this inevitably enforces decisions that systematically lead t…
CloudAttention: Efficient Multi-Scale Attention Scheme For 3D Point Cloud Learning
Mahdi Saleh, Yige Wang, Nassir Navab +2
Processing 3D data efficiently has always been a challenge. Spatial operations on large-scale point clouds, stored as sparse data, require extra cost. Attracted by the success of t…
DA Dataset: Toward Dexterity-Aware Dual-Arm Grasping
Guangyao Zhai, Yu Zheng, Ziwei Xu +6
In this paper, we introduce DA, the first large-scale dual-arm dexterity-aware dataset for the generation of optimal bimanual grasping pairs for arbitrary large objects. The da…
BFS-Net: Weakly Supervised Cell Instance Segmentation from Bright-Field Microscopy Z-Stacks
Shervin Dehghani, Benjamin Busam, Nassir Navab +1
Despite its broad availability, volumetric information acquisition from Bright-Field Microscopy (BFM) is inherently difficult due to the projective nature of the acquisition proces…
PhoCaL: A Multi-Modal Dataset for Category-Level Object Pose Estimation with Photometrically Challenging Objects
Pengyuan Wang, HyunJun Jung, Yitong Li +6
Object pose estimation is crucial for robotic applications and augmented reality. Beyond instance level 6D object pose estimation methods, estimating category-level pose and shape…
ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose Estimation
Yongzhi Su, Mahdi Saleh, Torben Fetzer +5
Establishing correspondences from image to 3D has been a key task of 6DoF object pose estimation for a long time. To predict pose more accurately, deeply learned dense maps replace…
Know your sensORs -- A Modality Study For Surgical Action Classification
Lennart Bastian, Tobias Czempiel, Christian Heiliger +4
The surgical operating room (OR) presents many opportunities for automation and optimization. Videos from various sources in the OR are becoming increasingly available. The medical…
Bending Graphs: Hierarchical Shape Matching using Gated Optimal Transport
Mahdi Saleh, Shun-Cheng Wu, Luca Cosmo +3
Shape matching has been a long-studied problem for the computer graphics and vision community. The objective is to predict a dense correspondence between meshes that have a certain…