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GROUP STAGE! ENCE vs Liquid – HIGHLIGHTS – ESL Pro League Season 20 | CS2



All about ESL Pro League Season 20

ESL Pro League – Season 20

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29 Comments

  7. @nalariveral

    I know it’s only been positive comments on ultimate since he debuted but I don’t think he’s being praised enough. This guy’s a beast. Why is he not being praised as a rookie like m0nesy, like donk, like siuhy, or even w0nderful did? He’s just as good if not better than most of these guys.

  11. @sneakholic

    01:05 Coach was not clapping for pistol round win but actually for not choking and taking another embarrassment…..😂😂😂

  16. @nishadhshah3267

    1. Start
    2. Input Low-Resolution Image
    • Receive a low-resolution image that needs super-resolution or personalized stylization.
    3. Add Gaussian Noise
    • Apply Gaussian noise to the input image for the initial noise representation in the diffusion process.
    4. Feature Extraction using UNet Encoder
    • Pass the noisy image through the UNet encoder.
    • Extract multi-scale features from the image and progressively downsample to obtain compressed representations.
    5. Apply Pixel-Aware Attention Mechanism
    • Use the pixel-aware attention mechanism to identify and focus on important regions or pixels.
    • Enhance the pixel-level details based on adaptive attention weights.
    6. Forward Diffusion Process
    • Gradually add noise to the image using the diffusion model.
    • Learn the noise distribution over multiple time steps to prepare for image reconstruction.
    7. Reverse Diffusion Process
    • Iteratively denoise the image from the noisy representation.
    • Reconstruct the high-resolution image step-by-step by reversing the diffusion process.
    8. Feature Refinement using UNet Decoder
    • Pass the denoised representation through the UNet decoder.
    • Use skip connections to combine high-level features from the encoder with low-level features to preserve fine details.
    9. Generate High-Resolution Image
    • Produce the final high-resolution image with enhanced details.
    10. Apply Personalized Stylization (Optional)
    • If stylization is requested, apply the user-defined style to the generated image.
    • Adjust the style parameters to blend the artistic style while retaining the original content.
    11. Output High-Resolution or Stylized Image
    • Output the final image, either as a super-resolved version or with personalized stylization.
    12. End

    Additional Details for Visual Clarity:

    • Decision Nodes:
    • After “Generate High-Resolution Image,” include a decision node: “Is Stylization Requested?”
    • If “Yes,” proceed to “Apply Personalized Stylization.”
    • If “No,” proceed to “Output High-Resolution Image.”
    • Annotations:
    • Label important steps like “UNet Encoder,” “Pixel-Aware Attention,” “Forward Diffusion,” and “Reverse Diffusion” clearly.
    • Use arrows to indicate the flow from one step to the next.

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