OneViewAll achieves 92.5% ADD-0.1 accuracy on LINEMOD for novel object 6D pose estimation using only one real reference view by integrating category, symmetry, and patch-level semantic priors in a projection-equivariant alignment.
Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography
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DM³-Nav delivers decentralized multi-agent semantic navigation for multimodal open-vocabulary multi-object tasks that matches centralized baselines in simulation and succeeds in real-world robot deployments.
Dual-interval motion extraction plus motion-guided attention improves small-object detection in UAV videos by separating target dynamics from ego-motion.
citing papers explorer
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OneViewAll: Semantic Prior Guided One-View 6D Pose Estimation for Novel Objects
OneViewAll achieves 92.5% ADD-0.1 accuracy on LINEMOD for novel object 6D pose estimation using only one real reference view by integrating category, symmetry, and patch-level semantic priors in a projection-equivariant alignment.
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DM$^3$-Nav: Decentralized Multi-Agent Multimodal Multi-Object Semantic Navigation
DM³-Nav delivers decentralized multi-agent semantic navigation for multimodal open-vocabulary multi-object tasks that matches centralized baselines in simulation and succeeds in real-world robot deployments.
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Decoupling Ego-Motion from Target Dynamics via Dual-Interval Motion Cues for UAV Detection
Dual-interval motion extraction plus motion-guided attention improves small-object detection in UAV videos by separating target dynamics from ego-motion.
- MAPRPose: Mask-Aware Proposal and Amodal Refinement for Multi-Object 6D Pose Estimation