Depth-Anything-3 is a collection of core model implementations for depth prediction, multi-view geometry estimation, and RGB-D spatial pipelines. It includes a monocular depth estimation model for predicting depth maps from single images or video, and a 3D Gaussian splatting generator that predicts parameters to synthesize high-fidelity novel views of a scene. The project provides a multi-view geometry estimator for calculating spatially consistent depth and camera poses across synchronized visual inputs. It also functions as a visual SLAM enhancement tool designed to reduce drift and improve
Dask is a parallel computing framework and distributed task scheduler designed to scale Python data science workflows from single machines to large clusters. It functions as a cluster resource manager that orchestrates computational logic by representing tasks and their dependencies as directed acyclic graphs. This architecture allows the system to automate the distribution of workloads across available hardware while managing complex execution requirements. The project distinguishes itself through a lazy evaluation engine that defers data operations until they are explicitly requested, enabl
Kornia is a differentiable computer vision library and cross-framework tensor vision toolset. It implements vision operations as differentiable tensors to enable integration into deep learning pipelines and supports the transpilation of operations across PyTorch, TensorFlow, JAX, and NumPy. The project provides specialized toolsets for geometric vision and stereo depth, including algorithms for 3D scene reconstruction, camera calibration, and pose estimation. It further distinguishes itself as a differentiable image augmentation framework, applying random geometric and color transformations w
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
Meshroom is a node-based photogrammetry software designed to transform collections of two-dimensional images into three-dimensional models and scene geometry. It provides a visual interface for constructing and managing modular data pipelines, allowing users to automate complex computer vision tasks such as feature extraction, depth map estimation, and mesh generation.
alicevision/meshroom 的主要功能包括：3D Reconstruction Pipelines, Reconstruction Tools, Camera Tracking, Feature Extraction, Nodal Workflow Designers, Distributed Computing Frameworks, Gaussian Splatting, Directed Acyclic Graph Execution Engines。
alicevision/meshroom 的开源替代品包括： bytedance-seed/depth-anything-3 — Depth-Anything-3 is a collection of core model implementations for depth prediction, multi-view geometry estimation,… dask/dask — Dask is a parallel computing framework and distributed task scheduler designed to scale Python data science workflows… kornia/kornia — Kornia is a differentiable computer vision library and cross-framework tensor vision toolset. It implements vision… facebookresearch/detectron2 — Detectron2 is a PyTorch computer vision framework and visual recognition platform designed for training and deploying… open-mmlab/mmsegmentation — MMSegmentation is an open-source semantic segmentation toolbox built on PyTorch that provides a modular, configurable… graphdeco-inria/gaussian-splatting — Gaussian Splatting is a computational framework designed to transform sparse sets of two-dimensional photographs into…