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facebookresearch/MaskFormerArchived

0
View on GitHub↗
1,461 stars·158 forks·Python·8 views

MaskFormer

Per-Pixel Classification is Not All You Need for Semantic Segmentation (NeurIPS 2021, spotlight)

Features

  • Object Detection and Segmentation - Per-pixel classification for semantic segmentation tasks.

Star history

Star history chart for facebookresearch/maskformerStar history chart for facebookresearch/maskformer

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with MaskFormer

These projects share indexed features with MaskFormer. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • wongkinyiu/yolov9WongKinYiu avatar

    WongKinYiu/yolov9

    9,534View on GitHub↗

    YOLOv9 is a real-time computer vision framework and deep learning model designed for image classification, object detection, and instance segmentation. It functions as both a vision model and a trainer, allowing for the optimization of neural network weights on custom datasets using single or multiple GPUs. The framework utilizes programmable gradient information to perform high-speed identification and location of multiple objects within images and video streams. It extends beyond bounding box detection to provide instance segmentation and panoptic segmentation, which labels every pixel in a

    Pythonyolov9
    View on GitHub↗9,534
  • facebookresearch/detectron2facebookresearch avatar

    facebookresearch/detectron2

    34,548View on GitHub↗

    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

    Python
    View on GitHub↗34,548
  • chenfei-wu/taskmatrixchenfei-wu avatar

    chenfei-wu/TaskMatrix

    34,082View on GitHub↗

    TaskMatrix is a multimodal AI chat interface and visual task orchestrator. It combines language models with visual recognition to enable the exchange, analysis, and modification of images within a conversational environment. The system coordinates multiple foundation models through orchestration pipelines that chain language, detection, and segmentation models. This allows for complex visual operations, such as using text instructions to guide image masking and executing modular inpainting workflows to edit specific image regions. The project includes a computer vision toolset for object det

    Python
    View on GitHub↗34,082
  • uminosachi/sd-webui-inpaint-anythingUminosachi avatar

    Uminosachi/sd-webui-inpaint-anything

    1,290View on GitHub↗

    This project is an integrated creative interface for image manipulation that combines generative canvas expansion, object segmentation, and diffusion-based inpainting. It functions as an extension for Stable Diffusion, providing a workflow to isolate specific elements and perform targeted content modifications through prompt-guided synthesis. The tool distinguishes itself by automating the creation of precise selection masks, allowing users to identify and isolate objects by pointing to them rather than manually drawing selections. By chaining segmentation models with generative diffusion pip

    Pythonai-artanythingdiffusers
    View on GitHub↗1,290
Compare all 15 related projects→

Frequently asked questions

What does facebookresearch/maskformer do?

Per-Pixel Classification is Not All You Need for Semantic Segmentation (NeurIPS 2021, spotlight)

What are the main features of facebookresearch/maskformer?

The main features of facebookresearch/maskformer are: Object Detection and Segmentation.

Which projects share features with facebookresearch/maskformer?

Projects with overlapping indexed features include: facebookresearch/detectron2 — Detectron2 is a PyTorch computer vision framework and visual recognition platform designed for training and deploying… wongkinyiu/yolov9 — YOLOv9 is a real-time computer vision framework and deep learning model designed for image classification, object… chenfei-wu/taskmatrix — TaskMatrix is a multimodal AI chat interface and visual task orchestrator. It combines language models with visual… uminosachi/sd-webui-inpaint-anything — This project is an integrated creative interface for image manipulation that combines generative canvas expansion,… wang-xinyu/tensorrtx — tensorrtx is a computer vision inference engine and model implementation library designed for graphics processor… hujiecpp/istr — ISTR: End-to-End Instance Segmentation with Transformers (https://arxiv.org/abs/2105.00637).