Kornia

@kornia_foss

kornia.org
Vrijeme pridruživanja: studeni 2019.
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  1. Prikvačeni tweet
    27. sij

    Kornia v0.2.0 is out ! We have introduced a new data augmentation module with strong GPU support, extended the set of color conversion algorithms, supporting GPU CI tests with v1.4.0, and much more. Happy coding !

    163 proslijeđena tweeta 517 korisnika označava da im se sviđa
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  2. prije 18 sati

    Check out our new tutorial about how to perform efficient data augmentation in videos with for the Deepfake Detection Challenge

    13 proslijeđenih tweetova 54 korisnika označavaju da im se sviđa
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  3. proslijedio/la je Tweet
    31. sij

    Our department website featured , which will be officially presented at

    4 proslijeđena tweeta 14 korisnika označava da im se sviđa
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  4. proslijedio/la je Tweet
    31. sij

    Don't miss our tutorial about local features at . Review of traditional methods, learned and mixed :) You will also learn cool stuff you can do combining and

    Our tutorial for modern matching methods, which focuses on differentiable & end to end techniques, and includes a practical session got accepted at ! A version will also be presented at with and . More details soon.
    4 proslijeđena tweeta 16 korisnika označava da im se sviđa
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  5. proslijedio/la je Tweet
    31. sij

    Our tutorial for modern matching methods, which focuses on differentiable & end to end techniques, and includes a practical session got accepted at ! A version will also be presented at with and . More details soon.

    We have two tutorials accepted at ! 1) "Local Features: From SIFT to Differentiable" with and . Detectors, descriptors, matching all this stuff.
    1 reply 16 proslijeđenih tweetova 39 korisnika označava da im se sviđa
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  6. proslijedio/la je Tweet
    29. sij

    Found solution, which is almost not hardware-dependent: group-conv for small kernels and reshape for large kernels. One more thing: it is important to benchmark both forward and backward paths speed-up

    1 reply 5 proslijeđenih tweetova 14 korisnika označava da im se sviđa
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  7. proslijedio/la je Tweet
    28. sij

    Note that if you need to be fast - use extract_patches_from_pyramid from instead. The code is the same, but it is on GPU :)

    Now you can install extract_patches with pip install extract_patches and have nicely antialiazed patches for your local features. Done with help of great nbdev by and , it is really amazing how nbdev simplifies life.
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    3 proslijeđena tweeta 11 korisnika označava da im se sviđa
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  8. proslijedio/la je Tweet
    27. sij

    Glad to see interfacing with . Such a bold step forward!

    0:25
    Kornia v0.2.0 is out ! We have introduced a new data augmentation module with strong GPU support, extended the set of color conversion algorithms, supporting GPU CI tests with v1.4.0, and much more. Happy coding !
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    3 proslijeđena tweeta 11 korisnika označava da im se sviđa
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  9. proslijedio/la je Tweet
    27. sij

    Kornia is a GPU accelerated computer vision library for . Link:

    0:25
    Kornia v0.2.0 is out ! We have introduced a new data augmentation module with strong GPU support, extended the set of color conversion algorithms, supporting GPU CI tests with v1.4.0, and much more. Happy coding !
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    58 proslijeđenih tweetova 281 korisnik označava da mu se sviđa
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  10. 27. sij

    Check the release notes here:

    2 proslijeđena tweeta 10 korisnika označava da im se sviđa
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  11. proslijedio/la je Tweet
    13. sij

    One positive thing from spending 3 days playing with bengali: my improvement for mxresnet architecture with function: MaxBlurPool2d from "Making CNN shift-invariant again" paper. RangerMiSHBlur -> 76% on Imagewoof vs 75% of RangerMiSH

    12 proslijeđenih tweetova 48 korisnika označava da im se sviđa
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  12. proslijedio/la je Tweet
    9. sij

    Attending this year's in Aspen ⛷️? Several CVC researchers will be sharing their latest work. Edgar Riba () will be presenting his work on Find the paper here👉

    2 proslijeđena tweeta 3 korisnika označavaju da im se sviđa
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  13. proslijedio/la je Tweet
    21. pro 2019.

    Kornia local features haven`t (yet!) reached vlfeat features performance in terms of quality -- it is surprisingly hard to implement classic stuff in differentiable and batchable way. But we are working on it :) 2/3

    1 reply 2 proslijeđena tweeta 6 korisnika označava da im se sviđa
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  14. proslijedio/la je Tweet
    21. pro 2019.

    Here is a code snippet, implementing quadratic interpolation of maximum location. It depends on batched torch.solve function 3/3

    2 proslijeđena tweeta 2 korisnika označavaju da im se sviđa
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  15. proslijedio/la je Tweet
    21. pro 2019.

    Update in local features : conv_quad_interp3d instead of conv_soft_argmax3d It does single iteration of quadratic interpolation of local response maximum location, similar as in SIFT or HesAff done. 1/2

    6 proslijeđenih tweetova 14 korisnika označava da im se sviđa
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  16. proslijedio/la je Tweet
    20. pro 2019.

    OpenCV-like library, but centered on GPU, for pytorch.

    Announcing that Kornia is now officially part of the ecosystem. Community is growing.
    5 proslijeđenih tweetova 20 korisnika označava da im se sviđa
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  17. proslijedio/la je Tweet
    9. stu 2019.

    Announcing that Kornia is now officially part of the ecosystem. Community is growing.

    9 proslijeđenih tweetova 17 korisnika označava da im se sviđa
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  18. proslijedio/la je Tweet
    20. pro 2019.

    Great and simple example using to share operators between frameworks

    We are moving towards full JIT support in . This is how easy it is to export kornia modules to through .
    5 proslijeđenih tweetova 12 korisnika označava da im se sviđa
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  19. proslijedio/la je Tweet
    20. pro 2019.

    We are moving towards full JIT support in . This is how easy it is to export kornia modules to through .

    3 proslijeđena tweeta 15 korisnika označava da im se sviđa
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  20. proslijedio/la je Tweet
    19. pro 2019.

    More posters at 2019 💪🏽! Edgar Riba ( ) is presenting "Kornia: an open source differentiable computer vision library for PyTorch".

    6 proslijeđenih tweetova 17 korisnika označava da im se sviđa
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