STDC-Seg
A real-time semantic segmentation approach for efficient scene understanding.
Discover the best AI tools to help you semantic segmentation.
A real-time semantic segmentation approach for efficient scene understanding.
ICNet for Real-Time Semantic Segmentation on High-Resolution Images.
Efficient and lightweight CNN architecture for mobile and edge devices.
A comprehensive set of computer vision transformations for data augmentation and manipulation in PyTorch.

A module providing access to various pre-built datasets for image classification, detection, segmentation, and more, designed for use with PyTorch.

Real-time semantic segmentation for efficient scene understanding.

A pure ConvNet model constructed entirely from standard ConvNet modules, designed for the 2020s.

Accelerating Industrial Computer Vision through Domain-Specific Large Vision Models and Data-Centric AI.

The AI-native data platform for data-centric computer vision development.

Enterprise-grade data labeling platform for high-performance computer vision and sensor fusion.

The industry-standard deep learning dataset and model suite for state-of-the-art scene recognition.

The performance-first computer vision augmentation library for high-accuracy deep learning pipelines.
Industrial-grade human body segmentation for real-time background removal and portrait matting.

Revolutionizing edge intelligence through Analog Compute-in-Memory technology for extreme power efficiency.