Topics / #semantic-segmentation

Semantic-segmentation projects on GitHub

Pixel-level object segmentation in computer vision

As of October 20, 2026, the most-starred Semantic-segmentation projects on GitHub are ultralytics (62.6K stars), detectron2 (34.9K stars) and label-studio (28.5K stars). GitHub.Locker tracks 18 Semantic-segmentation repositories with 329.3K stars combined. The fastest-growing on October 18 was VisionHOPE, with +33 stars in a day.

18Projects

329.3KStars in total

+115Stars in a day

Browse in the catalog →github.com/topics/semantic-segmentation ↗

Hot right now

Most stars gained in a day · Oct 18

+33

VisionHOPE

PSRben/VisionHOPE · ★ 1.3K

VisionHOPE is the official PyTorch implementation of a visual backbone built on self-referential nested learning (SRNL), supporting ImageNet-1K classification, COCO detection/instance segmentation, and ADE20K semantic segmentation.

+28

ultralytics

ultralytics/ultralytics · ★ 62.6K

Ultralytics YOLO is a family of state-of-the-art computer vision models (YOLO26, YOLO11, YOLOv8, etc.) covering object detection, instance segmentation, semantic segmentation, image classification, pose estimation, oriented object detection, depth estimation, and multi-object tracking in video.

+11

dinov2

facebookresearch/dinov2 · ★ 13.5K

DINOv2, a self-supervised visual feature learning method from Meta AI's FAIR team, shipped as PyTorch code and pretrained models. Its features plug into classifiers as simple as linear layers across many vision tasks, with no fine-tuning required.

+10

label-studio

HumanSignal/label-studio · ★ 28.5K

Label Studio is an open source data labeling and annotation tool: you label audio, text, images, videos, and time series in a browser UI and export the results in formats ready for ML training.

The all-time top

18 projects · by stars

#1 · ultralytics/ultralytics
ultralytics
Ultralytics YOLO is a family of state-of-the-art computer vision models (YOLO26, YOLO11, YOLOv8, etc.) covering object detection, instance segmentation, semantic segmentation, image classification, pose estimation, oriented object detection, depth estimation, and multi-object tracking in video.
62.6K
#2 · facebookresearch/detectron2
detectron2
Detectron2 is Facebook AI Research's next-generation library for object detection, segmentation and other visual recognition tasks, with state-of-the-art algorithms.
34.9K
#3 · HumanSignal/label-studio
label-studio
Label Studio is an open source data labeling and annotation tool: you label audio, text, images, videos, and time series in a browser UI and export the results in formats ready for ML training.
28.5K

4
deep-learning-for-image-processing
26.4KWZMIAOMIAO/deep-learning-for-image-processing · Python
A video-based deep learning course that walks through classic computer-vision architectures for image classification, object detection, segmentation and keypoint detection, pairing each network with a lecture and runnable code.
5
CVPR2026-Papers-with-Code
22.9Kamusi/CVPR2026-Papers-with-Code
A curated, continuously updated index of CVPR 2026 papers and their open-source code implementations, organized by computer vision topic (object detection, segmentation, 3D reconstruction, diffusion models, multimodal LLMs, etc.).
6
DeepLearning
17.8KMikoto10032/DeepLearning · Jupyter Notebook
A Chinese-language deep learning tutorial — a huge curated collection of links to courses, books, lecture notes, surveys and code, taking you from math basics through CNNs, GANs, RNNs and GNNs to Kaggle practice and interview prep.
7
cvat
17Kcvat-ai/cvat · Python
CVAT is an open-source, self-hosted data annotation platform for building labeled datasets from images, video, and 3D point clouds, used for computer vision and visual AI projects.
8
labelme
16.2Kwkentaro/labelme · Python
Labelme is a graphical image annotation tool written in Python: you draw polygons, rectangles, circles, lines and points on images to build labeled datasets for computer vision work.
9
Swin-Transformer
16.1Kmicrosoft/Swin-Transformer · Python
The official Microsoft implementation of the Swin Transformer paper and its follow-ups: a hierarchical vision Transformer that computes attention with shifted windows and serves as a general-purpose backbone for computer vision tasks.
10
yolov7
14.2KWongKinYiu/yolov7 · Jupyter Notebook
This is the official PyTorch implementation of YOLOv7, a real-time object detection model that achieved new state-of-the-art speed/accuracy results using a technique the authors call 'trainable bag-of-freebies'.
11
dinov2
13.5Kfacebookresearch/dinov2 · Jupyter Notebook
DINOv2, a self-supervised visual feature learning method from Meta AI's FAIR team, shipped as PyTorch code and pretrained models. Its features plug into classifiers as simple as linear layers across many vision tasks, with no fine-tuning required.
12
pytorch-grad-cam
13Kjacobgil/pytorch-grad-cam · Python
A Python package that implements many state-of-the-art Explainable AI (pixel attribution/Class Activation Map) methods for computer vision models, letting you visualize which parts of an image a model focuses on.
13
segmentation_models.pytorch
11.8Kqubvel-org/segmentation_models.pytorch · Python
A Python library for building image semantic segmentation models in PyTorch, with over 500 pretrained convolutional and transformer-based backbones.
14
Pytorch-UNet
11.7Kmilesial/Pytorch-UNet · Python
A PyTorch implementation of the U-Net convolutional network for semantic segmentation, customized for Kaggle's Carvana Image Masking Challenge on high-definition images.
15
awesome-semantic-segmentation
10.8Kmrgloom/awesome-semantic-segmentation
A curated list of resources for semantic segmentation: network architectures, papers, code implementations, datasets, benchmarks, annotation tools, and losses used in the field.
16
InternVL
10.2KOpenGVLab/InternVL · Python
A family of open-source multimodal chat models that understand images, video and text, positioned as an open alternative to GPT-4o. InternVL2.5-78B was the first open-source model to top 70% on the MMMU benchmark.
17
VisionHOPE
1.3KPSRben/VisionHOPE · Python
VisionHOPE is the official PyTorch implementation of a visual backbone built on self-referential nested learning (SRNL), supporting ImageNet-1K classification, COCO detection/instance segmentation, and ADE20K semantic segmentation.
18
nnUNet_att_position_correction
342qpuchen/nnUNet_att_position_correction · Python
This is the official PyTorch code for the MICCAI 2023 STS Challenge (3D tooth segmentation from CBCT scans) by team sdkxd, which extends nn-UNet with axial attention and a positional correction module to clean up abnormal segmentation points.