This is the Linux app named CutLER whose latest release can be downloaded as CutLERsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS:
CutLER
DESCRIPTION:
CutLER is an approach for unsupervised object detection and instance segmentation that trains detectors without human-annotated labels, and the repo also includes VideoCutLER for unsupervised video instance segmentation. The method follows a “Cut-and-LEaRn” recipe: bootstrap object proposals, refine them iteratively, and train detection/segmentation heads to discover objects across diverse datasets. The codebase provides training and inference scripts, model configs, and references to benchmarking results that report large gains over prior unsupervised baselines. It’s intended for researchers exploring self-supervised and unsupervised recognition, offering a practical path to scale beyond costly labeled corpora. The README links papers and gives a high-level overview of components and expected outputs, with pointers to demos and assets. The repository is actively starred and structured as a typical research release with license, contribution guidelines, and security policy.
Features
- Unsupervised object detection and instance segmentation
- VideoCutLER for unsupervised video instance segmentation
- Training and inference pipelines with configs
- Proposal bootstrapping and iterative refinement workflow
- Benchmarks and example results for comparison
- Research-friendly code structure and documentation
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/cutler.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.