MMD-Reg registers point clouds without correspondences by minimizing an MMD objective approximated via random Fourier features, solved with Levenberg-Marquardt and differentiated via the implicit function theorem for use as a neural network layer.
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Open3D: A Modern Library for 3D Data Processing
46 Pith papers cite this work. Polarity classification is still indexing.
46
Pith papers citing it
abstract
Open3D is an open-source library that supports rapid development of software that deals with 3D data. The Open3D frontend exposes a set of carefully selected data structures and algorithms in both C++ and Python. The backend is highly optimized and is set up for parallelization. Open3D was developed from a clean slate with a small and carefully considered set of dependencies. It can be set up on different platforms and compiled from source with minimal effort. The code is clean, consistently styled, and maintained via a clear code review mechanism. Open3D has been used in a number of published research projects and is actively deployed in the cloud. We welcome contributions from the open-source community.
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representative citing papers
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.
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.
2D Triangle Splatting uses 2D triangles instead of 3D Gaussians to enable differentiable optimization that yields opaque mesh-like reconstructions with competitive visual quality.
ViVo introduces a diverse multi-view volumetric video dataset with raw multi-camera RGB-depth data, calibration, masks, and point clouds to support reconstruction and compression research, with benchmarks highlighting limitations of current methods.
CSCD generalizes LS to continuous domain with CSCD-M using intrinsic triangulation for meshes and CSCD-PC using tufted Laplacians for point clouds, claiming to match or outperform priors on benchmarks.
LAPS improves incremental neural LiDAR mapping by combining reliability-based active pooling for sample retention with uncertainty-guided active sampling for optimization focus.
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.
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.
Introduces Multimodal-NF, a synchronized dataset of near-field CSI with RGB, LiDAR, and GPS data plus an open generator for low-altitude XL-MIMO research.
SPEAR-1 combines a 3D-enriched VLM with embodied control to match or exceed existing robotic foundation models using 20 times fewer robot demonstrations.
Spatial-MLLM adds a 3D spatial encoder initialized from a visual geometry model and space-aware frame sampling to MLLMs to improve spatial understanding and reasoning from purely 2D visual inputs.
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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.