CARD is a new multi-modal driving dataset delivering ~500K dense depth pixels per frame from challenging road topographies using stereo cameras and fused LiDARs over 110 km.
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Open3D: A Modern Library for 3D Data Processing
22 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 22representative citing papers
Manifold k-NN generalizes DP-NNS to k-NN queries on manifold point clouds via a recursive successor-list property, delivering 1-10x speedups and full dynamic support.
Paired-CSLiDAR benchmark and Residual-Guided Stratified Registration achieve 86% success at 0.75 m RMSE on 9,012 cross-source pairs by height-stratified ICP and confidence-gated selection.
PC2Model is a new public benchmark dataset combining simulated and real-world 3D point clouds with corresponding models to train and test registration methods.
ClipGStream enables scalable flicker-free reconstruction of long dynamic multi-view videos by performing stream optimization at the clip level with clip-independent spatio-temporal fields, residual anchor compensation, and inter-clip inherited anchors.
SEM-ROVER generates large multiview-consistent 3D urban driving scenes via semantic-conditioned diffusion on Σ-Voxfield voxel grids with progressive outpainting and deferred rendering.
A probabilistic validation framework with a novel modified area validation metric quantifies finite element model error for fusion heat sinks while separating it from aleatoric and epistemic experimental uncertainties.
Point cloud geometry is cast as a statistical manifold of per-point Gaussians, with POLI learning the mapping self-supervisedly to improve perception without labeled data.
A gradient-descent algorithm with level-set surface representation and dynamic point adjustment generates curvature-adaptive, locally regular point distributions on curved surfaces with low deviation from target spacing.
A new MAT simplification algorithm uses explicit surface correspondence tracking and priority-controlled edge collapses to preserve structural features like fillet alignments on discrete meshes.
PRIME is a five-level hierarchical equivariant graph model for proteins that uses physics-informed deterministic operators to exchange information across scales and achieves state-of-the-art results on fold classification and reaction class prediction.
A new online attack framework manipulates object poses in shared CAV perception data below detection thresholds, propagating errors to cause unsafe trajectory predictions and behaviors in up to 50% of tested scenarios while evading defenses.
DualViewMapDet fuses prior-traversal point cloud maps into camera features via dual perspective-view and bird's-eye-view encoding to improve 3D detection and tracking without LiDAR.
BiCICLe frames bimanual robot control as a multi-agent leader-follower problem with Arms' Debate and an LLM judge, achieving up to 71.1% success on 13 TWIN benchmark tasks without fine-tuning.
TouchAnything reconstructs accurate 3D object geometries from only a few tactile contacts by optimizing for consistency with a pretrained visual diffusion prior.
A coupled world-agent framework uses 3D Gaussian reconstruction and first-person RGB-D perception with iterative planning to enable goal-directed, collision-avoiding humanoid behavior in novel reconstructed scenes.
HandDreamer is the first zero-shot text-to-3D method for hands that uses MANO initialization, skeleton-guided diffusion, and corrective shape guidance to produce view-consistent models.
A monocular vision system estimates real-scale island area and coastline length with around 10% error using only place name or coordinates input via automated image capture, point cloud generation, and trajectory alignment.
A new PCR algorithm using probabilistic self-update local correspondence and line vector sets achieves superior time efficiency and at least 10% RMSE improvement over state-of-the-art methods.
Smartphone transillumination imaging paired with a neuroevolution-tuned ensemble model classifies chicken breast myopathies at 82.4% accuracy on 336 fillets, matching costly hyperspectral systems.
MeshOn composes two input meshes realistically without intersections by using VLM-based rigid initialization, attractive geometric losses, a barrier loss, and a diffusion prior for final deformation.
R3PM-Net delivers real-time point cloud registration with high accuracy on synthetic and real-world datasets through a global-aware lightweight architecture and new evaluation benchmarks.
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Towards Virtual Qualification in Nuclear Fusion: Demonstrating Probabilistic Model Validation on a High Heat Flux Component
A probabilistic validation framework with a novel modified area validation metric quantifies finite element model error for fusion heat sinks while separating it from aleatoric and epistemic experimental uncertainties.