computer-vision-13
Real-Time Semantic Segmentation
3260 papers • 126 benchmarks • 313 datasets
Semantic Segmentation is a computer vision task that involves assigning a semantic label to each pixel in an image. In Real-Time Semantic Segmentation, the goal is to perform this labeling quickly and accurately in real-time, allowing for the segmentation results to be used for tasks such as object recognition, scene understanding, and autonomous navigation. ( Image credit: TorchSeg )
(Image credit: Papersgraph)
Benchmarks
These leaderboards are used to track progress in real-time-semantic-segmentation-13
Trend
Dataset
Best Model
Actions
Cityscapes test
Cityscapes test
CamVid
CamVid
NYU Depth v2
NYU Depth v2
Libraries
iUse these libraries to find real-time-semantic-segmentation-13 models and implementations
16 papers 2,915
Datasets
Subtasks
No subtasks available.
