DA-RetinaNet VS Unsupervised-Semantic-Segmentation

Compare DA-RetinaNet vs Unsupervised-Semantic-Segmentation and see what are their differences.

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DA-RetinaNet Unsupervised-Semantic-Segmentation
2 1
59 386
- -
6.1 1.8
5 months ago almost 2 years ago
Python Python
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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DA-RetinaNet

Posts with mentions or reviews of DA-RetinaNet. We have used some of these posts to build our list of alternatives and similar projects.

Unsupervised-Semantic-Segmentation

Posts with mentions or reviews of Unsupervised-Semantic-Segmentation. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing DA-RetinaNet and Unsupervised-Semantic-Segmentation you can also consider the following projects:

datumaro - Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.

mmselfsup - OpenMMLab Self-Supervised Learning Toolbox and Benchmark

layout-parser - A Unified Toolkit for Deep Learning Based Document Image Analysis

Unsupervised-Classification - SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]

DA-Faster-RCNN - Detectron2 implementation of DA-Faster R-CNN, Domain Adaptive Faster R-CNN for Object Detection in the Wild

solo-learn - solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning

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

DiffCSE - Code for the NAACL 2022 long paper "DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings"

mmdetection - OpenMMLab Detection Toolbox and Benchmark

PASS - The PASS dataset: pretrained models and how to get the data

BCNet - Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]