Point Cloud
Point clouds are collections of 3D data points representing objects or scenes, primarily used for tasks like 3D reconstruction, object recognition, and autonomous navigation. Current research focuses on improving the efficiency and robustness of point cloud processing, employing techniques like deep learning (e.g., transformers, convolutional neural networks), optimal transport, and Gaussian splatting for tasks such as registration, completion, and compression. These advancements are crucial for applications ranging from robotics and autonomous driving to medical imaging and cultural heritage preservation, enabling more accurate and efficient analysis of complex 3D data.
Papers
Engineering LLM Powered Multi-agent Framework for Autonomous CloudOps
Kannan Parthasarathy, Karthik Vaidhyanathan, Rudra Dhar, Venkat Krishnamachari, Basil Muhammed, Adyansh Kakran, Sreemaee Akshathala, Shrikara Arun, Sumant Dubey, Mohan Veerubhotla, Amey Karan
Revisiting Birds Eye View Perception Models with Frozen Foundation Models: DINOv2 and Metric3Dv2
Seamie Hayes, Ganesh Sistu, Ciarán Eising
PSReg: Prior-guided Sparse Mixture of Experts for Point Cloud Registration
Xiaoshui Huang, Zhou Huang, Yifan Zuo, Yongshun Gong, Chengdong Zhang, Deyang Liu, Yuming Fang
3DGS-to-PC: Convert a 3D Gaussian Splatting Scene into a Dense Point Cloud or Mesh
Lewis A G Stuart, Michael P Pound
Efficiently Closing Loops in LiDAR-Based SLAM Using Point Cloud Density Maps
Saurabh Gupta, Tiziano Guadagnino, Benedikt Mersch, Niklas Trekel, Meher V. R. Malladi, Cyrill Stachniss
Representation Learning of Point Cloud Upsampling in Global and Local Inputs
Tongxu Zhang, Bei Wang
CL3DOR: Contrastive Learning for 3D Large Multimodal Models via Odds Ratio on High-Resolution Point Clouds
Keonwoo Kim, Yeongjae Cho, Taebaek Hwang, Minsoo Jo, Sangdo Han
Implicit Guidance and Explicit Representation of Semantic Information in Points Cloud: A Survey
Jingyuan Tang, Yuhuan Zhao, Songlin Sun, Yangang Cai
MRG: A Multi-Robot Manufacturing Digital Scene Generation Method Using Multi-Instance Point Cloud Registration
Songjie Han, Yinhua Liu, Yanzheng Li, Hua Chen, Dongmei Yang
Multi-modal classification of forest biodiversity potential from 2D orthophotos and 3D airborne laser scanning point clouds
Simon B. Jensen, Stefan Oehmcke, Andreas Møgelmose, Meysam Madadi, Christian Igel, Sergio Escalera, Thomas B. Moeslund
Impact of color and mixing proportion of synthetic point clouds on semantic segmentation
Shaojie Zhou, Jia-Rui Lin, Peng Pan, Yuandong Pan, Ioannis Brilakis
Imperceptible Adversarial Attacks on Point Clouds Guided by Point-to-Surface Field
Keke Tang, Weiyao Ke, Weilong Peng, Xiaofei Wang, Ziyong Du, Zhize Wu, Peican Zhu, Zhihong Tian