Some complex subject will fail, don't try hard.
prompt: ORBITCAM, the viewer orbit around the subject
BUT! works better if you describe!
ex: ORBITCAM, the viewer orbit around the subject, a shark and a woman swiming in a sea
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FAQ
Comments (11)
Is the v2 better or difference ? (and thx for this lora)
more data trained, kinda better, i still recomend using detailed description for the subject, for better generation.
How did you get the training data for this? Is it from other AI video generators? Or Wan itself?
i made with the help of https://civitai.com/models/2099912?modelVersionId=2375849
Very good LORA. Coolly working
can you pls pls do handheld camera moving/walking POV lora please!!!!
A very simple yet absolutely essential LoRA. It has literally saved us a huge chunk of work in 3D. Massive respect to the author!
Previously, when we didn’t have access to the real location where the deepfake was supposed to take place, we had to build an entire realistic 3D scene from photos, just like in CGI. Now we train the neural net on specific objects, generate images, run them through a 3D neural network for high-poly and retopology, then assemble photorealistic scenes based on that. Once again, huge thanks to the author! 😊
Glad to see there ain't only gooners around (even if i'm one myself haha)
v2 flat out doesn't work. Tested many prompts, models and different pictures and it never worked once. Took a chance and used v1 after seeing all the examples were listing that version and it worked right away.
Has anyone figured out a configuration that allows us to provide context of both front and back to the model (to avoid it hallucinating the flipside)?
Nope. This is nice but matrix effect only. I'm going to use it for last scene, characters are laying in the field, on their back, gently breathing, that may work. But for the rest, no. And to be fair it's normal, we will need a special tool to feed front side and rear of eveything before we can hallucinate a 360.
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Same model published on other platforms. May have additional downloads or version variants.