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Found 6 papers, 1 papers with code
Generalizing 6-DoF Grasp Detection via Domain Prior Knowledge
We focus on the generalization ability of the 6-DoF grasp detection method in this paper.
Sim-to-Real Grasp Detection with Global-to-Local RGB-D Adaptation
This paper focuses on the sim-to-real issue of RGB-D grasp detection and formulates it as a domain adaptation problem.
RGB-D Grasp Detection via Depth Guided Learning with Cross-modal Attention
Planar grasp detection is one of the most fundamental tasks to robotic manipulation, and the recent progress of consumer-grade RGB-D sensors enables delivering more comprehensive features from both the texture and shape modalities.
Double-Dot Network for Antipodal Grasp Detection
This paper proposes a new deep learning approach to antipodal grasp detection, named Double-Dot Network (DD-Net).
Visual and Semantic Knowledge Transfer for Large Scale Semi-supervised Object Detection
This is done by modeling the differences between the two on categories with both image-level and bounding box annotations, and transferring this information to convert classifiers to detectors for categories without bounding box annotations.
Large Scale Semi-Supervised Object Detection Using Visual and Semantic Knowledge Transfer
This is done by modeling the differences between the two on categories with both image-level and bounding box annotations, and transferring this information to convert classifiers to detectors for categories without bounding box annotations.
