2025年4月のポストまとめ

📊 概要

20件のポスト（リプライ除く）を3カテゴリに分類しました。

カテゴリ	件数	割合
🏗️ 3D再構成・SLAM	11	██████████ 55%
🚗 自動運転	6	█████ 30%
📄 論文紹介	3	███ 15%

🏆 人気トップ3

🥇 1位

RT	46
Like	232
Views	11000

MambaGlue: Fast and Robust Local Feature Matching With Mamba @ ICRA’25 > MambaGlue is a hybrid neural network combining the Mamba and the Transformer architectures to match local features.

🔗 ポストを見る

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🥈 2位

RT	32
Like	210
Views	13000

Roller Coaster SLAM Dataset The world’s first roller coaster SLAM dataset

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🥉 3位

RT	29
Like	187
Views	11000

[CVPR 2025] Any6D: Model-free 6D Pose Estimation of Novel Objects

🔗 ポストを見る

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📂 カテゴリ別ハイライト

🏗️ 3D再構成・SLAM

11件のポスト

MambaGlue: Fast and Robust Local Feature Matching With Mamba @ ICRA'25 > MambaGlue is a hybrid neural network combining the Mamba and the Transformer ... (♥ 232)

Roller Coaster SLAM Dataset The world's first roller coaster SLAM dataset (♥ 210)

• PE3R: Perception-Efficient 3D Reconstruction. Take 2 - 3 photos with your phone, upload them, wait a few minutes, and then start exploring your 3D wor… (♥ 150)

OpenLiDARMap Zero-Drift Point Cloud Mapping using Map Priors (♥ 115)

• LiteGS A refactored codebase for Gaussian Splatting. Faster(3.5x)!! Modular!! Pure Python or CUDA Extension (♥ 106)

🚗 自動運転

6件のポスト

• pointcloud_to_grid ROS 1 and ROS 2 node that converts sensor_msgs/PointCloud2 LIDAR data to nav_msgs/OccupancyGrid 2D map data based on intensity and … (♥ 105)

AKF-LIO: LiDAR-Inertial Odometry with Gaussian Map by Adaptive Kalman Filter (♥ 90)

tier4/AWML ML pipeline for Autoware (a.k.a. AWML) (♥ 71)

MDPCalib [RAL'24] Automatic Target-Less Camera-LiDAR Calibration from Motion and Deep Point Correspondences (♥ 69)

• GenZ_ICP_Optimized GenZ-ICP: SOTA robust LiDAR odometry (IEEE RA-L 2025) (Optimized version for reduced CPU usage) (♥ 60)

📄 論文紹介

3件のポスト

• [CVPR 2025] Any6D: Model-free 6D Pose Estimation of Novel Objects (♥ 187)
• awesome-rgbd-datasets This repository contains information for the paper “A Survey on RGB-D Datasets” and is a collaborative initiative to update the … (♥ 53)

Instruct-CLIP: Improving Instruction-Guided Image Editing with Automated Data Refinement Using Contrastive Learning (CVPR 2025) (♥ 48)

📋 全ポスト一覧

全20件を表示

| # | ポスト | RT | ♥ | 日付 | |--:|:-------|---:|--:|:-----| | 1 | [MambaGlue: Fast and Robust Local Feature Matching With Mamba @ ICRA'25 > MambaGl...](https://x.com/rsasaki0109/status/1915928693144535409) | 46 | 232 | 2025-04-26 | | 2 | [Roller Coaster SLAM Dataset The world's first roller coaster SLAM dataset](https://x.com/rsasaki0109/status/1913719908791357563) | 32 | 210 | 2025-04-19 | | 3 | [[CVPR 2025] Any6D: Model-free 6D Pose Estimation of Novel Objects](https://x.com/rsasaki0109/status/1911977782491414556) | 29 | 187 | 2025-04-15 | | 4 | [PE3R: Perception-Efficient 3D Reconstruction. Take 2 - 3 photos with your phone,...](https://x.com/rsasaki0109/status/1909030405803790802) | 23 | 150 | 2025-04-06 | | 5 | [OpenLiDARMap Zero-Drift Point Cloud Mapping using Map Priors](https://x.com/rsasaki0109/status/1915239279967740102) | 15 | 115 | 2025-04-24 | | 6 | [LiteGS A refactored codebase for Gaussian Splatting. Faster(3.5x)!! Modular!! Pu...](https://x.com/rsasaki0109/status/1915601676427284595) | 24 | 106 | 2025-04-25 | | 7 | [pointcloud_to_grid ROS 1 and ROS 2 node that converts sensor_msgs/PointCloud2 LI...](https://x.com/rsasaki0109/status/1911615393766203598) | 19 | 105 | 2025-04-14 | | 8 | [AKF-LIO: LiDAR-Inertial Odometry with Gaussian Map by Adaptive Kalman Filter](https://x.com/rsasaki0109/status/1914878410423517379) | 16 | 90 | 2025-04-23 | | 9 | [SKiD-SLAM Robust, Lightweight, and Distributed Multi-Robot LiDAR SLAM (SOLiD + K...](https://x.com/rsasaki0109/status/1910840271497048245) | 13 | 90 | 2025-04-11 | | 10 | [Fast-Loc-NeRF Fast Global Localization on Neural Radiance Field(ICRA 2025)](https://x.com/rsasaki0109/status/1914514504139825370) | 10 | 81 | 2025-04-22 | | 11 | [tier4/AWML ML pipeline for Autoware (a.k.a. AWML)](https://x.com/rsasaki0109/status/1910633938919346426) | 13 | 71 | 2025-04-11 | | 12 | [MDPCalib [RAL'24] Automatic Target-Less Camera-LiDAR Calibration from Motion and...](https://x.com/rsasaki0109/status/1911257943573741806) | 12 | 69 | 2025-04-13 | | 13 | [GenZ_ICP_Optimized GenZ-ICP: SOTA robust LiDAR odometry (IEEE RA-L 2025) (Optimi...](https://x.com/rsasaki0109/status/1916677271894872485) | 14 | 60 | 2025-04-28 | | 14 | [awesome-rgbd-datasets This repository contains information for the paper "A Surv...](https://x.com/rsasaki0109/status/1914158028905144806) | 12 | 53 | 2025-04-21 | | 15 | [Instruct-CLIP: Improving Instruction-Guided Image Editing with Automated Data Re...](https://x.com/rsasaki0109/status/1912340180360626560) | 10 | 48 | 2025-04-16 | | 16 | [D-LI-Init Dynamic Initialization for LiDAR-inertial SLAM(TMECH 2025)](https://x.com/rsasaki0109/status/1910170272227041580) | 8 | 48 | 2025-04-10 | | 17 | [PlaneRecTR: Unified Query Learning for 3D Plane Recovery from a Single View](https://x.com/rsasaki0109/status/1913378490742972771) | 9 | 47 | 2025-04-18 | | 18 | [scrstudio [CVPR 2025] A unified framework for Scene Coordinate Regression-based ...](https://x.com/rsasaki0109/status/1913069830670090413) | 7 | 36 | 2025-04-18 | | 19 | [RCPCC [ICRA 2025] Real-Time LiDAR Point Cloud Compression and Transmission for R...](https://x.com/rsasaki0109/status/1912613955815772634) | 3 | 19 | 2025-04-16 | | 20 | [autoware_objects_to_csv Convert various Autoware msg types to CSV file Use this ...](https://x.com/rsasaki0109/status/1909450352107438317) | 4 | 17 | 2025-04-08 |