Copertina

UOD: Unseen Object Detection in 3D Point Cloud

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Choi, Hyunjun, Um, Daeho, Jeong, Hawook
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Unsupervised Machine Learning for Detecting and Locating Human-Made Objects in 3D Point Cloud
di: Zhao, Hong, et al.
Pubblicazione: (2024)

Optimized CNNs for Rapid 3D Point Cloud Object Recognition
di: Lyu, Tianyi, et al.
Pubblicazione: (2024)

Enhancing Weakly Supervised Video Grounding via Diverse Inference Strategies for Boundary and Prediction Selection
di: Kim, Sunoh, et al.
Pubblicazione: (2025)

Study of Dropout in PointPillars with 3D Object Detection
di: Sun, Xiaoxiang, et al.
Pubblicazione: (2024)

Leveraging Generative AI Models to Explore Human Identity
di: Yeo, Yunha, et al.
Pubblicazione: (2025)

Unseen Object Reasoning with Shared Appearance Cues
di: Singh, Paridhi, et al.
Pubblicazione: (2024)

Unsupervised Change Detection for Space Habitats Using 3D Point Clouds
di: Santos, Jamie, et al.
Pubblicazione: (2023)

Finding Optimal Video Moment without Training: Gaussian Boundary Optimization for Weakly Supervised Video Grounding
di: Kim, Sunoh, et al.
Pubblicazione: (2026)

Explainable LiDAR 3D Point Cloud Segmentation and Clustering for Detecting Airplane-Generated Wind Turbulence
di: Qu, Zhan, et al.
Pubblicazione: (2025)

RaTrack: Moving Object Detection and Tracking with 4D Radar Point Cloud
di: Pan, Zhijun, et al.
Pubblicazione: (2023)

AMSP-UOD: When Vortex Convolution and Stochastic Perturbation Meet Underwater Object Detection
di: Zhou, Jingchun, et al.
Pubblicazione: (2023)

LmPT: Conditional Point Transformer for Anatomical Landmark Detection on 3D Point Clouds
di: Bastico, Matteo, et al.
Pubblicazione: (2026)

Self-Supervised Moving Object Segmentation of Sparse and Noisy Radar Point Clouds
di: Schwarzer, Leon, et al.
Pubblicazione: (2025)

Multimodal Object Query Initialization for 3D Object Detection
di: van Geerenstein, Mathijs R., et al.
Pubblicazione: (2023)

Towards Streaming LiDAR Object Detection with Point Clouds as Egocentric Sequences
di: Zhang, Mellon M., et al.
Pubblicazione: (2025)

PointNSP: Autoregressive 3D Point Cloud Generation with Next-Scale Level-of-Detail Prediction
di: Meng, Ziqiao, et al.
Pubblicazione: (2025)

MR-Occ: Efficient Camera-LiDAR 3D Semantic Occupancy Prediction Using Hierarchical Multi-Resolution Voxel Representation
di: Seong, Minjae, et al.
Pubblicazione: (2024)

Skeleton-based Robust Registration Framework for Corrupted 3D Point Clouds
di: Wang, Yongqiang, et al.
Pubblicazione: (2025)

Meltdown: Circuits and Bifurcations in Point-Cloud-Conditioned 3D Diffusion Transformers
di: Plattner, Maximilian, et al.
Pubblicazione: (2026)

CLIPoint3D: Language-Grounded Few-Shot Unsupervised 3D Point Cloud Domain Adaptation
di: Singha, Mainak, et al.
Pubblicazione: (2026)

Segmenting Known Objects and Unseen Unknowns without Prior Knowledge
di: Gasperini, Stefano, et al.
Pubblicazione: (2022)

DiffCloud: Real-to-Sim from Point Clouds with Differentiable Simulation and Rendering of Deformable Objects
di: Sundaresan, Priya, et al.
Pubblicazione: (2022)

Composite Convolution: a Flexible Operator for Deep Learning on 3D Point Clouds
di: Floris, Alberto, et al.
Pubblicazione: (2022)

CHARM3R: Towards Unseen Camera Height Robust Monocular 3D Detector
di: Kumar, Abhinav, et al.
Pubblicazione: (2025)

GeoMask3D: Geometrically Informed Mask Selection for Self-Supervised Point Cloud Learning in 3D
di: Bahri, Ali, et al.
Pubblicazione: (2024)

PointBA: Towards Backdoor Attacks in 3D Point Cloud
di: Li, Xinke, et al.
Pubblicazione: (2021)

PointLLM-R: Enhancing 3D Point Cloud Reasoning via Chain-of-Thought
di: Chen, Chaoqi, et al.
Pubblicazione: (2026)

Optimizing Sparse Convolution on GPUs with CUDA for 3D Point Cloud Processing in Embedded Systems
di: Luo, Chester, et al.
Pubblicazione: (2024)

How Many Tokens Do 3D Point Cloud Transformer Architectures Really Need?
di: Tran, Tuan Anh, et al.
Pubblicazione: (2025)

Spherical Mask: Coarse-to-Fine 3D Point Cloud Instance Segmentation with Spherical Representation
di: Shin, Sangyun, et al.
Pubblicazione: (2023)

Toward Availability Attacks in 3D Point Clouds
di: Zhu, Yifan, et al.
Pubblicazione: (2024)

Guiding Diffusion-Based Articulated Object Generation by Partial Point Cloud Alignment and Physical Plausibility Constraints
di: Kreber, Jens U., et al.
Pubblicazione: (2025)

Class-Aware PillarMix: Can Mixed Sample Data Augmentation Enhance 3D Object Detection with Radar Point Clouds?
di: Zhang, Miao, et al.
Pubblicazione: (2025)

SplAttN: Bridging 2D and 3D with Gaussian Soft Splatting and Attention for Point Cloud Completion
di: Li, Zhaoyang, et al.
Pubblicazione: (2026)

Point-RTD: Replaced Token Denoising for Pretraining Transformer Models on Point Clouds
di: Stone, Gunner, et al.
Pubblicazione: (2025)

Revisiting Out-of-Distribution Detection in LiDAR-based 3D Object Detection
di: Kösel, Michael, et al.
Pubblicazione: (2024)

Towards Training-Free Underwater 3D Object Detection from Sonar Point Clouds: A Comparison of Traditional and Deep Learning Approaches
di: Shaukat, M. Salman, et al.
Pubblicazione: (2025)

Methodology for an Analysis of Influencing Factors on 3D Object Detection Performance
di: Kuznietsov, Anton, et al.
Pubblicazione: (2024)

ActiveAnno3D -- An Active Learning Framework for Multi-Modal 3D Object Detection
di: Ghita, Ahmed, et al.
Pubblicazione: (2024)

Robustifying Point Cloud Networks by Refocusing
di: Levi, Meir Yossef, et al.
Pubblicazione: (2023)