Diffusion based model | Dense Prediction #llm #python #ai

Diffusion-based models are a powerful class of generative models that learn to generate or refine images by gradually removing noise. In dense prediction tasks, such as segmentation or depth estimation, diffusion models have recently been leveraged to predict pixel-level outputs across an entire image. These models work by iteratively refining a noisy image toward the desired output, making them well-suited for high-precision tasks where detailed, pixel-level information is essential.

By using a diffusion process, these models can generate complex structures with coherence and realism, making them popular in fields like computer vision and medical imaging. They also often produce results that are more robust to noise and variations in the input data compared to traditional approaches.

#diffusion #denseprediction #computervision #ImageSegmentation #GenerativeModels #genai #PixelLevelPrediction #machinelearning #ai #DepthEstimation #imageprocessing #datascience #deeplearning #visionai