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Point Clouds

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Papers

Mitigating Performance Discrepancy in Cross-Domain 3D Class-Incremental Learning

2026-09-04 · Jinge Ma, Gautham Vinod, Bruce Coburn, Jui-Feng Chi 외 arxiv

3D perception plays a crucial role in real-world applications such as autonomous driving, robotics, and AR/VR. In practical scenarios, 3D perception models need to continually adapt to newly emerging 3D object categories…

class-incremental learningAutonomous DrivingPoint Clouds

Dressing in Motion: A Human Motion-Aware Diffusion Policy for Robot-Assisted Dressing

2026-09-04 · Haoxiang Sun, Fangyuan Wang, Songhao Huang, Justina Y. W. Liu 외 arxiv

Robotic dressing assistance is a promising solution for supporting older adults with physical impairments in daily living. However, dressing under human motion remains challenging, as complex garment--human contact and o…

Point Clouds

SeqAlign3DVG: A Sequence-Aligned Benchmark and Voxel Reasoning Framework for 3D Visual Grounding

2026-08-31 · Yi Zhang, Yi Wang, Yueting Wu, Kaiyue Yang 외 arxiv

Image-based 3D visual grounding is critical for embodied agents, yet existing benchmarks suffer from loose text-observation alignment and neglect temporal ordering. We introduce SeqAlign3DVG, a novel benchmark dedicated …

Visual GroundingPoint Clouds

CedarCypress3D: an annotated UAV-LiDAR dataset of individual trees in planted cedar and cypress forests

2026-08-31 · Katsuto Shimizu, Fumiaki Kitahara, Tomohiro Nishizono, Hideki Saito 외 arxiv

Individual tree measurements derived from Light Detection and Ranging (LiDAR) mounted on Unmanned Aerial Vehicles (UAV) provide valuable information for forest inventory, ecosystem monitoring, and sustainable forest mana…

Instance SegmentationSemantic SegmentationPoint Clouds

Denoising-Aware Temporal Point Cloud Completion for 3D Crop Architecture Recovery and Phenotypic Trait Extraction

2026-08-28 · Mrudul Mittal, Soumyashree Kar arxiv

High-throughput phenotyping depends on accurate 3D reconstruction of plants across growth stages, yet the development and evaluation of temporal completion methods are limited by the lack of datasets with complete geomet…

Point Cloud Completion3D ReconstructionPoint Clouds

Beyond Pairwise Graphs in Science: Hypergraph Adaptive Wavelet Operators for Parametric PDEs

2026-08-28 · Rajat Sarkar, Venkataramana Runkana, Souvik Chakraborty arxiv

Physical systems are often modeled by solution operators that map input fields, parameters, geometries, or past states to steady or future physical states. Learning these maps is difficult, especially for time-dependent …

Point Clouds

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