bbox-visualizer VS graph-cut-ransac

Compare bbox-visualizer vs graph-cut-ransac and see what are their differences.

graph-cut-ransac

The Graph-Cut RANSAC algorithm proposed in paper: Daniel Barath and Jiri Matas; Graph-Cut RANSAC, Conference on Computer Vision and Pattern Recognition, 2018. It is available at http://openaccess.thecvf.com/content_cvpr_2018/papers/Barath_Graph-Cut_RANSAC_CVPR_2018_paper.pdf (by danini)
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bbox-visualizer graph-cut-ransac
2 5
374 400
- -
4.8 6.5
3 months ago about 1 month ago
Python C++
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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bbox-visualizer

Posts with mentions or reviews of bbox-visualizer. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-03-04.

graph-cut-ransac

Posts with mentions or reviews of graph-cut-ransac. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-02-28.

What are some alternatives?

When comparing bbox-visualizer and graph-cut-ransac you can also consider the following projects:

coco-viewer - Minimalistic COCO Dataset Viewer in Tkinter

second.pytorch - PointPillars for KITTI object detection

nuscenes-devkit - The devkit of the nuScenes dataset.

magsac - The MAGSAC algorithm for robust model fitting without using an inlier-outlier threshold

decoupled-style-descriptors - Code and data for ECCV 2020 paper Generating Handwriting via Decoupled Style Descriptors

diffgram - The AI Datastore for Schemas, BLOBs, and Predictions. Use with your apps or integrate built-in Human Supervision, Data Workflow, and UI Catalog to get the most value out of your AI Data.

sam - Code for the CVPR 2020 [ORAL] paper "SAM: The Sensitivity of Attribution Methods to Hyperparameters"

Unsupervised-Attention-guided-Image-to-Image-Translation - Unsupervised Attention-Guided Image to Image Translation

globox - A package to read and convert object detection datasets (COCO, YOLO, PascalVOC, LabelMe, CVAT, OpenImage, ...) and evaluate them with COCO and PascalVOC metrics.

stylegan2-pytorch - Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement