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@peterom15,737 subscribers

Open Source AI Art hypeman w/ @banodoco | Tools for artistic expression w/ @Reigh_Art | 👫🐕 w/ @hannahsubmarine. Aspiring 2nd Renaissance Man.

Shorts

The progress of the Animatediff community over the past 10 months has been miraculous - see attached! Now, closed startups like Krea are taking the fruits of all this effort - so I'd like to tell the story of how we got here & what people who believe in open source can do.

The progress of the Animatediff community over the past 10 months has been miraculous - see attached! Now, closed startups like Krea are taking the fruits of all this effort - so I'd like to tell the story of how we got here & what people who believe in open source can do.

166,604 просмотров

The meme-power of video-editing with Wan will be a force to be reckoned with Excellent examples by Illuminati Reptilien:

The meme-power of video-editing with Wan will be a force to be reckoned with Excellent examples by Illuminati Reptilien:

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Woke up today to see spacepxl trained a model on top of Wan to achieve SOTA performance in deblurring w/ an approach that will generalise to all kinds of video control tasks - upscaling, canny, video inpainting, etc. I love the open source AI art/banodoco community so much

Woke up today to see spacepxl trained a model on top of Wan to achieve SOTA performance in deblurring w/ an approach that will generalise to all kinds of video control tasks - upscaling, canny, video inpainting, etc. I love the open source AI art/banodoco community so much

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I believe that StoryDiffusion has the potential to be Animatediff's complex motion sister-model! While AD is amazing for granular control, micro-motion and all kinds of abstract motion, it fails at complex realistic motion - walking, human movements, cars, etc. StoryDiffusion seems very promising for this + also has characteristics that will likely make the community very receptive to it and likely to extend its capabilities: 2) Appealing base-model results - likely to get the community excited - feels like significantly better realistic motion than AD 2) Modular - their approach is built with a number of components that can be combined and taken apart - it works by generating consistent images, then animating them together - each of these stages can likely be upgraded, used and influenced in different ways. 3) Flexible - they demonstrate a bunch of different conditioning options 4) Likely easy on RAM - it's based on SD 1.5 + authors mention precautions to reduce RAM consumption 5) Built to plug into the existing ecosystem - e.g. the fact that it works with the SD1.5 ecosystem will give it a huge advantage! While it's very early to say - e.g. the video model hasn't even been released yet! - it does seem very promising. With 9 months of SD1.5/Animatediff-esque progress improving every element of it, I can see an an extremely extended version of this beating Sora + running for a fraction of the compute resources on a consumer GPU. Together with Animatediff to drive the micro-motions and abstract stuff, it could produce be extraordinary/otherworldly/insane/beautiful stuff. This is the first open video model I've been excited about since Animatediff - though cautiously optimistic! Link here:

I believe that StoryDiffusion has the potential to be Animatediff's complex motion sister-model! While AD is amazing for granular control, micro-motion and all kinds of abstract motion, it fails at complex realistic motion - walking, human movements, cars, etc. StoryDiffusion seems very promising for this + also has characteristics that will likely make the community very receptive to it and likely to extend its capabilities: 2) Appealing base-model results - likely to get the community excited - feels like significantly better realistic motion than AD 2) Modular - their approach is built with a number of components that can be combined and taken apart - it works by generating consistent images, then animating them together - each of these stages can likely be upgraded, used and influenced in different ways. 3) Flexible - they demonstrate a bunch of different conditioning options 4) Likely easy on RAM - it's based on SD 1.5 + authors mention precautions to reduce RAM consumption 5) Built to plug into the existing ecosystem - e.g. the fact that it works with the SD1.5 ecosystem will give it a huge advantage! While it's very early to say - e.g. the video model hasn't even been released yet! - it does seem very promising. With 9 months of SD1.5/Animatediff-esque progress improving every element of it, I can see an an extremely extended version of this beating Sora + running for a fraction of the compute resources on a consumer GPU. Together with Animatediff to drive the micro-motions and abstract stuff, it could produce be extraordinary/otherworldly/insane/beautiful stuff. This is the first open video model I've been excited about since Animatediff - though cautiously optimistic! Link here:

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Videos

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Today I'm announcing the themes for our upcoming open source AI art competition, The Arca Gidan Prize! The meta-theme for this edition is Time. Our goal is to push people toward the unconventional. We've all seen many AI movie trailers, commercials and music videos - but what can you do with AI that's genuinely new and different? What was impossible before? How can you push open models beyond what people expect? Without further ado, here are the sub-themes: 🔄 Déjà Vu "This has happened before — or has it? That uncanny shimmer when moments echo: the glitch, the loop. When time spirals back through existence and ripples with recognition." 🌸 The Briefness of Bloom "A moment when something is perfectly itself — just before it fades. The cherry blossom at peak. The golden hour before dusk. So luminous as it slips away, already a memory." ⏱️ Traveling Through Time "Traveling through time — backward, forward, sideways. The time traveler, the archaeologist, the prophet. Journeys to moments that never were or haven't happened yet." For full details on prizes and rules, check out: - The Arca Gidan Discord: - The website: As mentioned before, the current prize fund is $50k, paid for by the fees I received from the $dataclaw token. Any further fees I receive will be added to the prize fund - we'll keep adding $1k prizes for each full $1k we receive. Finally, please enjoy this theme trailer by Hannah Submarine:

POM

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