Zero-shot image segmentation with CLIPSeg

CLIPSeg introduces a zero-shot image segmentation model that leverages the CLIP architecture to perform segmentation tasks without the need for task-specific training data. The model utilizes a transformer-based architecture and achieves competitive performance on standard segmentation benchmarks, demonstrating the ability to generalize across diverse datasets. This approach allows practitioners to effectively apply image segmentation in scenarios with limited labeled data, enhancing the flexibility and scalability of segmentation applications in AI.