Awesome GitHub Repositories3D

Detectron2 is a PyTorch computer vision framework and visual recognition platform designed for training and deploying models for object detection, image segmentation, and visual recognition. It provides a research-oriented environment for training complex vision models with multi-GPU acceleration. The project includes a specialized object detection library for identifying and locating multiple objects via bounding boxes, as well as an image segmentation toolkit for creating pixel-level masks through instance, semantic, and panoptic segmentation. Additionally, it features a human pose estimati

Grounded-Segment-Anything is a suite of specialized tools for multimodal visual analysis, text-based segmentation, and generative image editing. It integrates text-to-bounding-box detection and high-precision image segmentation masks to function as a text-based image segmenter and an automated visual labeling tool. The project enables text-driven image editing by identifying objects through natural language to perform inpainting and element replacement. It further extends visual analysis into three dimensions, allowing for 3D human reconstruction and the generation of 3D bounding boxes from t

CenterNet est un framework de détection d'objets par points centraux et un pipeline de vision par ordinateur en temps réel. Il identifie les objets et les poses en prédisant les points centraux au lieu d'utiliser des boîtes d'ancrage (anchor boxes). Le système fonctionne comme un estimateur de boîtes englobantes 3D, un modèle d'estimation de pose humaine et un outil de détection d'objets en temps réel. Il traite le placement des articulations et les emplacements des objets comme des problèmes de détection de points centraux pour localiser les entités dans les images et l'espace tridimensionnel. Les capacités couvrent la détection d'objets 3D, l'estimation de points clés humains et l'analyse vidéo en direct. Le pipeline utilise un processus d'inférence feedforward à étape unique pour effectuer une analyse continue sur des webcams ou des fichiers vidéo.

Espectre is an edge machine learning framework and motion detection platform that uses Wi-Fi Channel State Information to identify human presence and movement. It functions as a sensing toolkit for ESP32 microcontrollers, enabling the detection of motion through walls without the use of cameras or wearables. The project distinguishes itself by executing compact neural network classifiers and mathematical detection algorithms directly on the microcontroller. It utilizes a MicroPython runtime to allow for the prototyping and deployment of sensing logic and wireless signal processing algorithms

BEVFormer is a perception framework that transforms multi-camera images into bird's-eye-view representations for autonomous driving. It functions as a multi-camera vision pipeline that integrates multiple camera streams into a single unified spatial perspective to facilitate environmental understanding. The system implements a transformer-based architecture that employs query-based feature extraction and spatiotemporal networks to aggregate spatial image features and temporal historical data. It uses recurrent temporal accumulation to maintain a persistent memory of the scene across consecuti