SegGPT: Segmenting everything in context [Explained]

CVPR 2023 has brought together significant advancements in computer vision, particularly with the emergence of generalist models like SegGPT that can solve a range of segmentation tasks in images and videos via in-context inference. SegGPT outperforms previous models such as Painter and specialist networks like Volumetric Aggregation with Transformers (VAT) in one-shot and few-shot segmentation tasks, achieving strong abilities to segment in and out-of-domain targets both qualitatively and quantitatively. The model's success is attributed to its ability to learn through in-context coloring, context ensembling, and in-context tuning, allowing it to generalize well across diverse segmentation tasks and datasets. SegGPT can be used for AI-assisted labelling, reducing annotation workload and improving quality, consistency, and speed of annotations. With its open-source code and demo available on Hugging Face, researchers and developers can explore the potential of SegGPT in various applications.

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