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Xiaohongshu Tech REDtech

May 10, 2024 · Artificial Intelligence

SIF3D: Sense‑Informed Forecasting of 3D Human Motion with Multimodal Attention

SIF3D is a scene‑aware 3D human motion forecasting framework that fuses observed motion, 3D point‑cloud scenes, and gaze through novel ternary intention‑aware and semantic‑coherence‑aware attention mechanisms, encoding with PointNet++ and Transformers, and decoding with a graph‑convolutional network, achieving state‑of‑the‑art results on GIMO and GTA‑1M benchmarks.

3D scene understandingCVPR2024Computer Vision

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SIF3D: Sense‑Informed Forecasting of 3D Human Motion with Multimodal Attention

Python Programming Learning Circle

May 5, 2024 · Artificial Intelligence

Python Implementation of DBSCAN and KMeans for Point Cloud Clustering and Tracking with Hungarian Matching

This article presents a Python project that reads point‑cloud data from CSV files, applies DBSCAN and KMeans clustering, extracts cluster features, and uses the Hungarian algorithm to match clusters across frames for tracking, complete with full source code and result visualization.

ClusteringDBSCANData Processing

0 likes · 13 min read

Python Implementation of DBSCAN and KMeans for Point Cloud Clustering and Tracking with Hungarian Matching

Python Programming Learning Circle

Apr 13, 2022 · Fundamentals

Using Open3D for 3D Data Processing: From Depth Maps to Point Clouds and Surface Reconstruction

This tutorial introduces the Open3D library, shows how to install it, convert depth maps to point clouds, visualize facial point clouds, perform point‑cloud segmentation and clustering, and apply surface reconstruction methods such as Poisson, alpha shapes, and ball‑pivoting using Python code.

3D processingOpen3Dpoint cloud

0 likes · 12 min read

Using Open3D for 3D Data Processing: From Depth Maps to Point Clouds and Surface Reconstruction

Amap Tech

Jun 25, 2021 · Frontend Development

Design and Implementation of the Eagle.gl Web 3D Engine for High-Definition Map Rendering

The Eagle.gl Web 3D engine, built atop Three.js, provides a unified 2D/3D GIS platform that efficiently loads, renders, and edits massive point‑cloud, vector, and model map data with real‑time LOD, GPU picking, DEM terrain integration, and configurable styling, supporting AMap’s HD‑map production and future autonomous‑driving simulation.

3D renderingGISThree.js

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Design and Implementation of the Eagle.gl Web 3D Engine for High-Definition Map Rendering

Amap Tech

Mar 12, 2021 · Fundamentals

MTA Problem in High‑Precision LiDAR Data and Its Correction Algorithms

The article describes how high‑frequency LiDAR scanners on precision mapping vehicles suffer from Multi‑Time‑Around (MTA) errors—mis‑assigning distant returns to near ranges—and explains both internal laser strategies (continuity assumption and variable‑period emission) and a four‑step neighborhood‑weighting algorithm that reliably corrects these artifacts, restoring accurate point‑clouds for automated map generation.

Data ProcessingLiDARMTA

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MTA Problem in High‑Precision LiDAR Data and Its Correction Algorithms

DataFunTalk

Mar 5, 2020 · Artificial Intelligence

High‑Precision Mapping and Localization Technologies for Autonomous Driving

This article explains the principles, components, generation process, and challenges of high‑precision topological and point‑cloud maps, and describes satellite‑based, map‑based, and fused high‑precision localization methods that underpin perception, prediction, planning, and control in autonomous driving systems.

SLAMautonomous drivinghigh-precision mapping

0 likes · 9 min read

High‑Precision Mapping and Localization Technologies for Autonomous Driving

Amap Tech

Nov 14, 2019 · Artificial Intelligence

Technical Evolution of Ground Marking Recognition for High‑Precision Maps

AMap’s ground‑marking recognition has progressed from simple threshold methods to advanced deep‑learning pipelines—including two‑stage R‑FCN, cascade detectors with local regression, corner‑point and segmentation hybrids, and LiDAR‑based 3‑D PointRCNN—achieving over 99 % recall and sub‑5 cm positional accuracy for high‑precision map production.

Computer Visiondeep learningground marking

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Technical Evolution of Ground Marking Recognition for High‑Precision Maps

Tencent Cloud Developer

Oct 22, 2019 · Game Development

Key Technologies of Immersive Media in the 5G Era: 3D, Point Cloud, and Compression

With 5G accelerating video traffic, immersive media relies on advanced 3D representation, efficient point‑cloud and video‑based compression, standardized containers, and selective streaming to enable realistic VR/AR experiences across gaming, autonomous driving, and broadcasting, while Tencent’s lab drives standards and future XR applications.

3D5GVR

0 likes · 12 min read

Key Technologies of Immersive Media in the 5G Era: 3D, Point Cloud, and Compression