8 papers
WaterSplat-SLAM: Photorealistic Monocular SLAM in Underwater Environment
Kangxu Wang, Shaofeng Zou, Chenxing Jiang +4
Underwater monocular SLAM is a challenging problem with applications from autonomous underwater vehicles to marine archaeology. However, existing underwater SLAM methods struggle t…
MG-Grasp: Metric-Scale Geometric 6-DoF Grasping Framework with Sparse RGB Observations
Kangxu Wang, Siang Chen, Chenxing Jiang +3
Single-view RGB-D grasp detection remains a common choice in 6-DoF robotic grasping systems, which typically requires a depth sensor. While RGB-only 6-DoF grasp methods has been st…
Diffusion-Based Depth Inpainting for Transparent and Reflective Objects
Tianyu Sun, Dingchang Hu, Yixiang Dai +1
Transparent and reflective objects, which are common in our everyday lives, present a significant challenge to 3D imaging techniques due to their unique visual and optical properti…
Butter: Frequency Consistency and Hierarchical Fusion for Autonomous Driving Object Detection
Xiaojian Lin, Wenxin Zhang, Yuchu Jiang +7
Hierarchical feature representations play a pivotal role in computer vision, particularly in object detection for autonomous driving. Multi-level semantic understanding is crucial…
Efficient End-to-End 6-Dof Grasp Detection Framework for Edge Devices with Hierarchical Heatmaps and Feature Propagation
Kaiqin Yang, Yixiang Dai, Guijin Wang +1
6-DoF grasp detection is critically important for the advancement of intelligent embodied systems, as it provides feasible robot poses for object grasping. Various methods have bee…
Region-aware Grasp Framework with Normalized Grasp Space for Efficient 6-DoF Grasping
Siang Chen, Pengwei Xie, Wei Tang +3
A series of region-based methods succeed in extracting regional features and enhancing grasp detection quality. However, faced with a cluttered scene with potential collision, the…