{"total":22,"rows":[{"id":"2110.03336","title":"Frame Averaging for Invariant and Equivariant Network Design","created":"2021-10-07","cited_by_count":168,"area":null},{"id":"2109.00182","title":"You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors","created":"2021-09-01","cited_by_count":68,"area":null},{"id":"2112.01741","title":"Frame Averaging for Equivariant Shape Space Learning","created":"2021-12-03","cited_by_count":19,"area":null},{"id":"2205.15210","title":"The Devil is in the Pose: Ambiguity-free 3D Rotation-invariant Learning via Pose-aware Convolution","created":"2022-05-30","cited_by_count":18,"area":null},{"id":"2409.00353","title":"RI-MAE: Rotation-Invariant Masked AutoEncoders for Self-Supervised Point Cloud Representation Learning","created":"2024-08-31","cited_by_count":15,"area":null},{"id":"2209.05924","title":"SVNet: Where SO(3) Equivariance Meets Binarization on Point Cloud Representation","created":"2022-09-13","cited_by_count":10,"area":null},{"id":"2403.11113","title":"Local-consistent Transformation Learning for Rotation-invariant Point Cloud Analysis","created":"2024-03-17","cited_by_count":6,"area":null},{"id":"2108.12790","title":"RPR-Net: A Point Cloud-based Rotation-aware Large Scale Place Recognition Network","created":"2021-08-29","cited_by_count":5,"area":null},{"id":"2301.00149","title":"Rethinking Rotation Invariance with Point Cloud Registration","created":"2022-12-31","cited_by_count":5,"area":null},{"id":"2303.03101","title":"CRIN: Rotation-Invariant Point Cloud Analysis and Rotation Estimation via Centrifugal Reference Frame","created":"2023-03-06","cited_by_count":4,"area":null},{"id":"2312.07039","title":"Open-Pose 3D Zero-Shot Learning: Benchmark and Challenges","created":"2023-12-12","cited_by_count":4,"area":null},{"id":"2306.11406","title":"Stable and Consistent Prediction of 3D Characteristic Orientation via Invariant Residual Learning","created":"2023-06-20","cited_by_count":3,"area":null},{"id":"2209.11916","title":"A Simple Strategy to Provable Invariance via Orbit Mapping","created":"2022-09-24","cited_by_count":2,"area":null},{"id":"2302.09907","title":"General Rotation Invariance Learning for Point Clouds via Weight-Feature Alignment","created":"2023-02-20","cited_by_count":2,"area":null},{"id":"2402.01331","title":"A general framework for rotation invariant point cloud analysis","created":"2024-02-02","cited_by_count":2,"area":null},{"id":"2502.07505","title":"Efficient Continuous Group Convolutions for Local SE(3) Equivariance in 3D Point Clouds","created":"2025-02-11","cited_by_count":2,"area":null},{"id":"2211.08250","title":"SPE-Net: Boosting Point Cloud Analysis via Rotation Robustness Enhancement","created":"2022-11-15","cited_by_count":1,"area":null},{"id":"2305.07814","title":"Cloud-RAIN: Point Cloud Analysis with Reflectional Invariance","created":"2023-05-13","cited_by_count":1,"area":null},{"id":"2408.15643","title":"RIDE: Boosting 3D Object Detection for LiDAR Point Clouds via Rotation-Invariant Analysis","created":"2024-08-28","cited_by_count":1,"area":null},{"id":"2112.12345","title":"Revisiting Transformation Invariant Geometric Deep Learning: An Initial Representation Perspective","created":"2021-12-23","cited_by_count":0,"area":null},{"id":"2511.08240","title":"Hierarchical Direction Perception via Atomic Dot-Product Operators for Rotation-Invariant Point Clouds Learning","created":"2025-11-11","cited_by_count":0,"area":null},{"id":"2512.02496","title":"Attention-guided reference point shifting for Gaussian-mixture-based partial point set registration","created":"2025-12-02","cited_by_count":0,"area":null}],"next_cursor":null}