Can someone ELI5 what this does? I read the abstract and tried to find differences in the provided examples, but I don't understand (and don't see) what the "photorealistic" part is.
Imagine history documentaries where they take an old photo and free objects from the background and move them round giving the illusion of parallax movement. This software does that in less than a second, creating a 3D model that can be accurately moved (or the camera for that matter) in your video editor. It's not new, but this one is fast and "sharp".
Until your comment I didn't realise I'd also read it wrong (despite getting the gist of it). Attempted rephrase of the original sentence:
Imagine history documentaries where they take an old photo, free objects from the background, and then move them round to give the illusion of parallax.
Takes a 2D image and allows you to simulate moving the angle of the camera with correct-ish parallax effect and proper subject isolation (seems to be able to handle multiple subjects in the same scene as well)
I guess this is what they use for the portrait mode effects.
It turns a single photo into a rough 3D scene so you can slightly move the camera and see new, realistic views. "Photorealistic" means it preserves real textures and lighting instead of a flat depth effect. Similar behavior can be seen with Apple's Spatial Scene feature in the Photos app: https://files.catbox.moe/93w7rw.mov
From a single picture it infers a hidden 3D representation, from which you can produce photorealistic images from slightly different vantage points (novel views).
I just want to emphasize that this is not a NERF where the model magically produces an image from an angle and then you ask "ok but how did you get this?" and it throws up its hands and says "I dunno, I ran some math and I got this image" :D.
Black Mirror episode portraying what this could do: https://youtu.be/XJIq_Dy--VA?t=14. If Apple ran SHARP on this photo and compared it to the show, that would be incredible.
Agreed, this is a terrible presentation. The paper abstract is bordering on word salad, the demo images are meaningless and don’t show any clear difference to the previous SotA, the introduction talks about “nearby” views while the images appear to show zooming in, etc.
In Chapter D.7 they describe: "The complex reflection in water is interpreted by the network as a distant mountain, therefore the water surface is broken."
This is really interesting to me because the model would have to encode the reflection as both the depth of the reflecting surface (for texture, scattering etc) as well as the "real depth" of the reflected object. The examples in Figure 11 and 12 already look amazing.
Apple's Spatial Scene in the Photos app shows similar behavior, turning a single photo into a small 3D scene that you can view by tilting the phone. Demo here: https://files.catbox.moe/93w7rw.mov
This is incredibly cool. It's interesting how it fails in the section where you need to in-paint. SVC seems to do that better than all the rest, though not anywhere close to the photorealism of this model.
Is there a similar flow but to transform either a video/photo/NeRF of a scene into a tighter, minimal polygon approximation of it. The reason I ask is that it would make some things really cool. To make my baby monitor mount I had to knock out the calipers and measure the pins and this and that, but if I could take a couple of photos and iterate in software that would be sick.
You'd still need one real measurement at least: this might get proportions right if background can be clearly separated, but the absolute size of an object can be worlds apart.
Have a look through the rest of the images. TMPI has some pretty obvious shortcomings in a lot of them.
1. Sky looks jank
2. Blurry/warped behind the horse
3. The head seems to move a lot more than the body. You could argue that this one is desirable
4. Bit of warping and ghosting around the edges of the flowers. Particularly noticeable towards the top of the image.
5. Very minor but the flowers move as if they aren't attached to the wall
I'm confused, does it actually generate environments from photographs? I can't view the galleries since I didn't sign up for emails but all of the gallery thumbnails are AI, not photos.
Works great, model file is 2.8 GB, on M2 rendering took a few seconds, result is guassian .ply file but repo implementation requires CUDA card to render video, I have used one of webgl live renderers from here https://github.com/scier/MetalSplatter?tab=readme-ov-file#re...
That is really impressive. However, it was a bit confusing at first because in the koala example at the top, the zoomed in area is only slightly bigger than the source area. I wonder why they didn't make it 2-3x as big in both axes like they did with the others.
I understand AI for reasoning, knowledge, etc. I haven't figured out how anyone wants to spend money for this visual and video stuff. It just seems like a bad idea.
Simulation. It takes a lot of effort today to bring up simulations in various fields. 3 D programming is very nontrivial and asset development is extremely expensive. If I have a workspace I can take a photo of and just use it to generate a 3d scene I can then use it in simulations to test ideas out. This is particularly useful in robotics and industrial automation already.
This specific paper is pretty different to the kind of photo/video generation that has been hyped up in recent years. In this case, I think this might be what they're using for the iOS spatial wallpaper feature, which is arguably useless but is definitely an aesthetic differentiator to Android devices. So, it's indirectly making money.
Do people not spend on entertainment? Commercials? It's probably less of a bad idea than knowledge. AI giving a bad visual has less negatives than giving the wrong knowledge leading to the wrong decision.
"Unsplash > Gen3C > The fly video" is nightmare fuel. View at your own risk: https://apple.github.io/ml-sharp/video_selections/Unsplash/g...
Early AI „everything turns into dog heads“ vibes. Beautiful.
I miss those. Anyone know if it's still possible to get the models etc. needed to generate them?
I wish there was an archive of all those melty dreamscapes.
https://m.youtube.com/watch?v=DgPaCWJL7XI&t=1s&pp=2AEBkAIB0g...
https://www.youtube.com/watch?v=X0oSKFUnEXc
san check, 1d10
Seth Brundle has entered the chat.
Can someone ELI5 what this does? I read the abstract and tried to find differences in the provided examples, but I don't understand (and don't see) what the "photorealistic" part is.
Imagine history documentaries where they take an old photo and free objects from the background and move them round giving the illusion of parallax movement. This software does that in less than a second, creating a 3D model that can be accurately moved (or the camera for that matter) in your video editor. It's not new, but this one is fast and "sharp".
Gaussian splashing is pretty awesome.
What are free objects?
The "free" in this case is a verb. The objects are freed from the background.
Until your comment I didn't realise I'd also read it wrong (despite getting the gist of it). Attempted rephrase of the original sentence:
Imagine history documentaries where they take an old photo, free objects from the background, and then move them round to give the illusion of parallax.
I'd suggest a different verb like "detach" or "unlink".
> Imagine history documentaries where they take an old photo, free objects from the background
Even using commas, if you leave the ambiguous “free” I suggest you prefix “objects” with “the” or “any”.
Takes a 2D image and allows you to simulate moving the angle of the camera with correct-ish parallax effect and proper subject isolation (seems to be able to handle multiple subjects in the same scene as well)
I guess this is what they use for the portrait mode effects.
It turns a single photo into a rough 3D scene so you can slightly move the camera and see new, realistic views. "Photorealistic" means it preserves real textures and lighting instead of a flat depth effect. Similar behavior can be seen with Apple's Spatial Scene feature in the Photos app: https://files.catbox.moe/93w7rw.mov
From a single picture it infers a hidden 3D representation, from which you can produce photorealistic images from slightly different vantage points (novel views).
There's nothing "hidden" about the 3d represenation. It's a point cloud (in meters) with colors, and a guess at the the "camera" that produced it.
(I am oversimplifying).
"Hidden" or "latent" in a context like this just means variables that the algo is trying to infer because it doesn't have direct access to them.
Hidden in the sense of neural net layers. I mean intermediary representation.
Right.
I just want to emphasize that this is not a NERF where the model magically produces an image from an angle and then you ask "ok but how did you get this?" and it throws up its hands and says "I dunno, I ran some math and I got this image" :D.
It makes your picture 3D. The "photorealistic" part is "it's better than these other ways".
Black Mirror episode portraying what this could do: https://youtu.be/XJIq_Dy--VA?t=14. If Apple ran SHARP on this photo and compared it to the show, that would be incredible.
Or if you prefer Blade Runner: https://youtu.be/qHepKd38pr0?t=107
Agreed, this is a terrible presentation. The paper abstract is bordering on word salad, the demo images are meaningless and don’t show any clear difference to the previous SotA, the introduction talks about “nearby” views while the images appear to show zooming in, etc.
In Chapter D.7 they describe: "The complex reflection in water is interpreted by the network as a distant mountain, therefore the water surface is broken."
This is really interesting to me because the model would have to encode the reflection as both the depth of the reflecting surface (for texture, scattering etc) as well as the "real depth" of the reflected object. The examples in Figure 11 and 12 already look amazing.
Long tail problems indeed.
Apple's Spatial Scene in the Photos app shows similar behavior, turning a single photo into a small 3D scene that you can view by tilting the phone. Demo here: https://files.catbox.moe/93w7rw.mov
It‘s awful and often creates a blurry mess in the imaginated space behind the object.
Photoshop content aware fill could do equally or better many years ago.
cuda gpu only
https://github.com/apple/ml-sharp#rendering-trajectories-cud...
Interestingly Apple’s own models don’t work on MPS. Well, I guess you just have to wait for few years..
No, model works without CUDA then you have .ply that you can drop into gaussian splatter viewer like https://sparkjs.dev/examples/#editor
CUDA is needed to render side scrolling video, but there is many ways to do other things with result.
This is specifically only for video rendering. The model itself works across GPU, CPU, and MPS.
> photorealistic 3D representation from a single photograph in less than a second
I want to see with people
Impressive but something doesn't feel right to me.. Possibly too much sharpness, possibly a mix of cliches, all amplified at once.
This is incredibly cool. It's interesting how it fails in the section where you need to in-paint. SVC seems to do that better than all the rest, though not anywhere close to the photorealism of this model.
Is there a similar flow but to transform either a video/photo/NeRF of a scene into a tighter, minimal polygon approximation of it. The reason I ask is that it would make some things really cool. To make my baby monitor mount I had to knock out the calipers and measure the pins and this and that, but if I could take a couple of photos and iterate in software that would be sick.
You'd still need one real measurement at least: this might get proportions right if background can be clearly separated, but the absolute size of an object can be worlds apart.
Is there a link with some sample gaussian splat files coming from this model? I couldn't find it.
Without that that it's hard to tell how cherry-picked the NVS video samples are.
EDIT: I did it myself, if anyone wants to check out the result (caveat, n=1): https://github.com/avaer/ml-sharp-example
This is great for turning a photo into a dynamic-IPD stereo pair + allows some head movement in VR.
Ah and the dynamic IPD component preserves scale?
So this is the secret sauce behind Cinematic mode. The fake bokeh insanity has reached its climax!
As well as their "Spatial Scene" mode for lock screen images, which synthesizes a mild parallax effect as you move the phone.
It's available for everyday photos, portraits, everything, not just lock screens.
you can also press the button while viewing a photo in the Photos app to see this.
Enhance! https://www.youtube.com/watch?v=LhF_56SxrGk
I thought this was going to be the Super Troopers version
TMPI looks just as good if not better.
Have a look through the rest of the images. TMPI has some pretty obvious shortcomings in a lot of them.
1. Sky looks jank 2. Blurry/warped behind the horse 3. The head seems to move a lot more than the body. You could argue that this one is desirable 4. Bit of warping and ghosting around the edges of the flowers. Particularly noticeable towards the top of the image. 5. Very minor but the flowers move as if they aren't attached to the wall
Disagree - look at the sky in the seaweed shot. It doesn't quite get the depth right in anything, and the edges of things look off.
Agreed. The head of the fly also seems to have weird depth.
See also Spaitial[0] which announced today full 3D environment generation from a single image
[0]https://www.spaitial.ai/
Requires email to view anything, that’s sad
The best I've seen so far is Marble from World Labs, though that gives you a full 360 environment and takes several minutes to do so.
I'm confused, does it actually generate environments from photographs? I can't view the galleries since I didn't sign up for emails but all of the gallery thumbnails are AI, not photos.
> I'm confused, does it actually generate environments from photographs?
It’s a website that collects people’s email addresses
Why are all their examples of rooms?
Why no landscape or underwater scenes or something in space, etc.?
Constrained environments are much simpler.
I believe this company is doing image (or text) -> off the shelf image model to generate more views -> some variant of gaussian splatting.
So they aren't really "generating" the world as one might imagine.
Works great, model file is 2.8 GB, on M2 rendering took a few seconds, result is guassian .ply file but repo implementation requires CUDA card to render video, I have used one of webgl live renderers from here https://github.com/scier/MetalSplatter?tab=readme-ov-file#re...
That is really impressive. However, it was a bit confusing at first because in the koala example at the top, the zoomed in area is only slightly bigger than the source area. I wonder why they didn't make it 2-3x as big in both axes like they did with the others.
I understand AI for reasoning, knowledge, etc. I haven't figured out how anyone wants to spend money for this visual and video stuff. It just seems like a bad idea.
Simulation. It takes a lot of effort today to bring up simulations in various fields. 3 D programming is very nontrivial and asset development is extremely expensive. If I have a workspace I can take a photo of and just use it to generate a 3d scene I can then use it in simulations to test ideas out. This is particularly useful in robotics and industrial automation already.
This specific paper is pretty different to the kind of photo/video generation that has been hyped up in recent years. In this case, I think this might be what they're using for the iOS spatial wallpaper feature, which is arguably useless but is definitely an aesthetic differentiator to Android devices. So, it's indirectly making money.
Do people not spend on entertainment? Commercials? It's probably less of a bad idea than knowledge. AI giving a bad visual has less negatives than giving the wrong knowledge leading to the wrong decision.