Showing 4 open source projects for "pixel"

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  • 1
    Recurrent Interface Network (RIN)

    Recurrent Interface Network (RIN)

    Implementation of Recurrent Interface Network (RIN)

    ...The big surprise is that the generations can reach this level of fidelity. Will need to verify this on my own machine. Additionally, we will try adding an extra linear attention on the main branch as well as self-conditioning in the pixel space. The insight of being able to self-condition on any hidden state of the network as well as the newly proposed sigmoid noise schedule are the two main findings.
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  • 2
    Diffusers-Interpret

    Diffusers-Interpret

    Model explainability for Diffusers

    diffusers-interpret is a model explainability tool built on top of Diffusers. Model explainability for Diffusers. Get explanations for your generated images. Install directly from PyPI. It is possible to visualize pixel attributions of the input image as a saliency map. diffusers-interpret also computes these token/pixel attributions for generating a particular part of the image. To analyze how a token in the input prompt influenced the generation, you can study the token attribution scores. You can also check all the images that the diffusion process generated at the end of each step. ...
    Downloads: 0 This Week
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  • 3
    min(DALL·E)

    min(DALL·E)

    min(DALL·E) is a fast, minimal port of DALL·E Mini to PyTorch

    ...The largest logit is subtracted from the logits to avoid infs. The logits are then divided by the temperature. If is_seamless is true, the image grid will be tiled in token space not pixel space.
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  • 4
    CIPS-3D

    CIPS-3D

    3D-aware GANs based on NeRF (arXiv)

    3D-aware GANs based on NeRF (arXiv). This repository contains the code of the paper, CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis. The problem of mirror symmetry refers to the sudden change of the direction of the bangs near the yaw angle of pi/2. We propose to use an auxiliary discriminator to solve this problem. Note that in the initial stage of training, the auxiliary discriminator must dominate the generator more than the main discriminator does. ...
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