yolact
A fully convolutional neural network for real-time instance segmentation, achieving high speed and accuracy on COCO.
What is yolact?
YOLACT is a deep learning model designed for real-time instance segmentation, which involves detecting and precisely outlining each distinct object in an image. It solves the problem of performing this computationally intensive task quickly enough for live applications, such as autonomous driving or interactive systems, by using a single, fully convolutional network architecture.
Computer vision researchers and engineers who need to implement fast and accurate instance segmentation in real-time applications, including video processing, robotics, and augmented reality.
Developers choose YOLACT for its unique combination of high frame rates and competitive accuracy, enabled by its simple yet effective protonet-based mask generation, avoiding the complexity and latency of two-stage models like Mask R-CNN.
Overview
A simple, fully convolutional model for real-time instance segmentation.
Use Cases
Best For
- Real-time video object segmentation and tracking
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