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3D Ken Burns Effect from a Single Image
- simonholland 7y agoI am a broadcast film editor PBS, Nat Veo BBC etc..many shows need this parallax effect to engage viewers with stills. At present the After effects production of this effect is time consuming and expensive. Please keep in touch with me if you bring an app to market or offer a service to process our 3D stills. Simonhollandfilms@gmail.com
- adammenges 7y agoGreat job! Love this.
- sniklaus 7y agoPaper: https://arxiv.org/abs/1909.05483 https://arxiv.org/abs/1909.05483 Website: http://sniklaus.com/kenburns http://sniklaus.com/kenburns
- alphakappa 7y agoThe results look impressive. Is the code or a tool available that would enable others to try it out on their images?
- myth_buster 7y agoI may be wrong in thinking that given two researchers are working at Adobe, the plan probably is to keep it proprietary and put it in one of their software.
- sniklaus 7y agoI am planning to release the code as well as the dataset but have yet to get approval to do so. If the work is done by an intern, then Adobe is usually fairly open in terms of sharing the work.
- Wowfunhappy 7y agoThank you, I'd really love to play with this!
- myth_buster 7y agoThanks for clarifying. Looking forward to the digging into codebase.
- puranjay 7y agoI'd love to play around with it for a music video (non commercial)!
- canada_dry 7y agoI'm doing a video slideshow for my niece's wedding in a couple weeks and would love to add this effect to a bunch of their photos (without spending a usual hours-and-hours in photoshop). Hope you're able to release it ASAP!
- kissickas 7y agoLove your personal website.
- sniklaus 7y agoThank you for you kind words! I moved away from having separate websites for each project and am currently trying to bring all my projects to my personal website. I just added the Mini Chess game last night, which used to be an Android app.
- sorenjan 7y agoReally impressive results. Is your "Context-aware Synthesis for Video Frame Interpolation" available as an implementation somewhere? It looks really good. I skimmed the paper about the Ken Burns effect, and if you don't mind I have some questions. I hope I didn't miss the answers in the paper itself, I'll be sure to read it more carefully when time permits. 1. The loss function for the depth estimation is Ldepth=0.0001·Lord+Lgrad. Is Lgrad much bigger than Lord by design or will this basically make Lord tiny and almost unecessary? How did you arrive at this number and not a magnitude bigger or smaller? 2. How are you rendering the point cloud, like tiny discs in free space? When I think of point clouds I think of the typical LIDAR output renderings, but your results are continuous images, or video frames. Are the points rendered to an image plane and the result then interpolated? And a couple more general ones: 1. Are all other depth estimation techniques other than NN obsolete now? Is there no point in estimating intrinsic camera parameters and epipolar lines when the state of the art seems to be to input one or more images into a NN and let it produce the depth for you? 2. How do you decide how the NN should look like, with various downsampling layers, convolutions, etc. I've seen people start with pretrained networks and retrain them, but how do you build a novel network based on the input and desired output?
- sniklaus 7y agoI unfortunately did not get the approval to release the context-aware frame interpolation, but one of my older works is open source for research purposes: https://github.com/sniklaus/pytorch-sepconv https://github.com/sniklaus/pytorch-sepconv 1. I am not sure about the scale of the individual loss functions anymore, my apologies. I determined the combination of the two losses via a simple grid search and seeing what works best (plus / minus a magnitude did not make that much of a difference). 2. The points are just splatted to an image plane, more advanced point cloud rendering techniques would be better though. There is no video frame interpolation, each individual frame in the output video is a rendering of the point cloud from a different camera perspective. 3. I am not sure about multi-view stereo, COLMAP still seems like the state of the art for that. But neural networks definitely outperform classic techniques for single image depth estimation. 4. Common architectures just did not do as well as I was hoping for so I tried about 1500 model architectures. I started with an architecture that intuitively seemed right and then gradually explored / refined alterations of it. It ultimately was a lot of trial and error.
- sniklaus 7y agoI just got the daily email from my server with some metrics. It has experienced over 500 gigabytes of traffic in the last few hours and the video is only 3 megabytes in size. I definitely did not expect such a HN-effect.
- FreeHugs 7y agoThe video is 180 MB. So 500 GB are about 2800 full video downloads.
- sniklaus 7y agoOnly very few people in comparison watched the full video. Here are the logs for the content server from yesterday 5 PM PST, covering the previous 24 hours (search for /kenburns/promo.mp4): https://pastebin.com/4zTxL2aw https://pastebin.com/4zTxL2aw
- sniklaus 7y agoI see your point now. This post originally pointed to the teaser video and not the project website (I do not know who changed that, must have been an admin): http://content.sniklaus.com/kenburns/promo.mp4 http://content.sniklaus.com/kenburns/promo.mp4
- FreeHugs 7y agoWhat does this line mean: /kenburns/promo.mp4 | GET | 175574 | 33.4183748571803 That the video was watched 175574 times? That would indeed be a lot!
- sniklaus 7y agoThat means that there were 175574 HTTP GET requests, but my guess is that if someone fast-forwards that that might trigger another request. So the actual number of views may be a little lower.
- nacs 7y agoMaybe upload the video to Youtube? The video is barely loading here.
- zekarlos 7y agolooks good!
- covercash 7y agoI’ve manually done that in the past using Photoshop and multiple layers in Final Cut Pro, it was very time consuming. I wonder if this method requires you to isolate the layers manually.
- sniklaus 7y agoI was watching a lot of tutorials like that when I started working on the project. The shown results were created fully automatically, one can optionally refine the camera path though. You can find more information on that in the video on my website.
- amayne 7y agoCool. But that’s not what we call the Ken Burns Effect in the industry. This is 2.5 D parallax shift as seen in the documentary The Kid Stays in the Picture. Ken Burns Effect is panning and zooming to highlight features in a photo then fading into another.
- onemoresoop 7y agoPretty much what I thought as well. But cool nonetheless.
- sgt 7y agoPerhaps it would also be worth mentioning Ken Burns and his documentaries. They're absolutely worth watching and gives BBC a run for its money. Perhaps start with The West and then move on to Civil War. My personal favorite was perhaps the one on Jazz, made in 2001.
- bgeeek 7y agoI'm not sure that they give the BBC a run for its money - you're talking about quite a lot of Beeb output ;-) I agree that they are of an unusually high standard.
- billfruit 7y agoBBC documentaries, many of them atleast are having a reputation beyond what they deserve I think, often times the real information in them is sparse, and they present overtly simplistic narratives, with too much padding.
- bgeeek 7y agoIn comparison to what, though? It's easy to knock the Beeb, but compare the output (TV, Radio, and Web) to anything vaguely similar and you will probably appreciate the quality. They're not just making docus, it's so much more. Funnily enough, the Beeb aired the Burns Vietnam, too.
- davidmurdoch 7y agoReminds me of this gimbal-shot portrait-video parallax effect: https://youtu.be/Ryu4hp-HbwU https://youtu.be/Ryu4hp-HbwU (which was probably somewhat inspired by the Ken's Burns Effect)
- sniklaus 7y agoThose look nice! The premise of the project was to only use a single image as an input in order to be applicable to existing footage. Without this constraint, more stunning effects like the portrait-video parallax become possible. I am sure we will see more exciting work like this in the future!
- bonestamp2 7y agoThat's awesome, great tutorial. Another fun one is dolly zoom, which is pretty easy. Some of the DJI drones can even do it automatically: https://www.youtube.com/watch?v=MC7hkMR0hBs https://www.youtube.com/watch?v=MC7hkMR0hBs
- kd3 7y agoIncredible. Amazing. Holy shit.
- sniklaus 7y agoThis comment made me smile, thank you. :)
- kd3 7y agoI imagine it must feel great to be a modern wizard. This is magic.
- sniklaus 7y agoIt is the result of a lot of work (a lot) and I truly believe everyone in my situation with the right mindset would have been able to achieve it. Being a Ph.D. student and having a chance to do internships at companies like Adobe or Google does sometimes feel like a privilege though, so I understand that not many are in the same situation.
- whalesalad 7y agoI've always wondered if Apple was using technology like this for the movie covers in the Apple TV store, since they have a parallax effect. For those who don't know what I am talking about, the remote control has a touchpad on it, so as you wiggle your finger around (while a title is selected) the cover will move on a 3D axis w/ your finger until you use enough force to move to the next title. Figured there would be a relatively straightforward way to separate the layers w/ software. But only certain titles have the effect ... so I would imagine the studios provide a layered asset that can get composed together.
- bonestamp2 7y agoYes, I've submitted artwork to iTunes and they want (but don't require) a layered file for the artwork to create that parallax effect. You'll notice most just have the Title and (other text) as moveable layers, which is easy since those were probably created as separate layers when the artwork was created to begin with. The background artwork is typically static, although I suspect this tool will be included in photoshop at some point at which time it will make it much easier to give this effect to backgrounds too. Here are some specs if you're interested (there are various different docs depending on which assets you're submitting, this is just one example): https://help.apple.com/itc/videoaudioassetguide/#/itc0c10422b9 https://help.apple.com/itc/videoaudioassetguide/#/itc0c10422...
- whalesalad 7y agoOh rad, thanks for the link!
- sniklaus 7y agoThank you both for the pointers! Our research on the 3D Ken Burns effect could be used to automate this, but the quality is still a little spotty. Some results look great, some have obvious artifacts. An automated deployment would thus either need to improve the overall quality or be able to detect artifacts in order to fallback to the 2D result for those.
- 7y ago
- anon1m0us 7y agoYou'll notice the effect isn't as good at about 7 seconds into the movie where the green grass between the bride and her maids moves with the bride. Why does the algorithm think that is part of her, rather than the background?
- sniklaus 7y agoEstimating the scene geometry from a single image is highly challenging and remains an unsolved problem. As such, you can find subtle artifacts like this in most of the results. The artifact that you are referring to stems from a geometry adjustment step in which we make sure that salient objects like humans or animals are on a plane in the 3D space. This requires image segmentation which is also highly challenging and may lead to parts of the background being assigned to the segmented foreground object and vice versa.
- anon1m0us 7y agoCould you not use something like the "magic wand" selection tool in image editing programs? Doesn't the dramatic color difference indicate it's not part of the same object? I thought maybe it grabbed it because it was the same color as the bouquet she is holding, but that is entirely within the white of her dress.
- sniklaus 7y agoThere definitely is room for improvement. Our proposed framework uses Mask R-CNN for object segmentation. However, Mask R-CNN only as a resolution of 28x28 pixels for the object masks if I remember correctly (which is then resized to the actual resolution of the object in the image). So there are a lot of limitations from that alone.
- czr 7y agoif you haven't already seen it, https://github.com/dbolya/yolact https://github.com/dbolya/yolact generates very sharp instance masks very quickly, may be of interest
- k__ 7y agoDoes this work real-time?
- sniklaus 7y agoIt takes two to three seconds to process the input image and can subsequently synthesize each frame in the output video in real time. This makes it possible for the user to adjust the camera path and see the result in real time. Feel free to have a look at the video on the website for an example of this.
- gibi555 7y agolike, thanks))
- JonathanFly 7y agoNot bad but monocular depth estimation has gotten pretty good all around. I made these similar images with basically no expertise, no manual mapping, just trying random single image depth projects from github. I kind of just went with whatever I could get running quickly, didn't even evaulate the quality other than cases where it obviously didn't work. (Sorry for linking a million tweets but I didn't put these on a blog or anything, that's the only place they exist.) Your version does look better though! But I was impressed I could just run random images through depth estimates and get anything cool like this. https://twitter.com/jonathanfly/status/1156799136987013120 https://twitter.com/jonathanfly/status/1156799136987013120 https://twitter.com/jonathanfly/status/1153383325974896646 https://twitter.com/jonathanfly/status/1153383325974896646 https://twitter.com/jonathanfly/status/1154472832249860100 https://twitter.com/jonathanfly/status/1154472832249860100 https://twitter.com/jonathanfly/status/1153120643040337925 https://twitter.com/jonathanfly/status/1153120643040337925 I would love to your method take on some Escher paintings, can you try it for me?
- sniklaus 7y agoThey look nice, thank you for sharing! It seems like the input images that you used are paintings. I am not sure how well our depth estimation would work on those, definitely something to try out.
- JonathanFly 7y ago> It seems like the input images that you used are paintings. Yeah, I love trying things that aren't supposed to work! They often do work and surprise you, or fail in interesting ways.
- nunodonato 7y agoCool. I have a Fiverr service to make these for whoever wants to transform a normal photo into a 2.5D one. But it's hand made, so I guess this can make the whole thing more accessible to anyone
- sniklaus 7y agoOur work focuses on physically correct depth. We have noticed that such effects created by professional artists emphasize the parallax to an extend that is not physically correct. As such, artists still seem to know best how to animate a catchy parallax effect.
- logicallee 7y agoFor easy clicking the link at the end of the video is: http://sniklaus.com/kenburns http://sniklaus.com/kenburns very interesting!
- rolltiide 7y agoGreat! I was thinking about doing this for years Every time I see an awesome landscape in person I think about whats missing from capturing that for other people to experience and I concluded it came down to depth perception and how our eyes dart around to create a composite experience resulting in ever slight shifts of depth A 2D image cant capture that, but this seems a lot closer and its great it can use a 2D image as a base
- sniklaus 7y agoI wholeheartedly agree with you and believe that depth perception is a key aspect that is is missing in the status quo of viewing still images!
- TazeTSchnitzel 7y agoI've seen this effect done to a single still image before, but presumably it was done by hand somehow. Specifically, in the “Kony 2012” video (remember that?)
- sniklaus 7y agoThe effect itself is actually not too uncommon. It is just very tedious and time-consuming to do manually since it requires segmenting the elements in the scene, arranging them in a 3D space, filling in any holes and specifying a virtual camera trajectory.
- seanalltogether 7y agoThanks for clarifying this. My roommate used to do this in after effects 10 years ago, so I couldn't understand what the demo video was attempting to showcase.
- wilsmex 7y agoI did a simple tutorial on YouTube that illustrates the basic methods for the hand done 2.5D parallax effect in Photoshop: https://www.youtube.com/watch?v=giE4SuC9qWc https://www.youtube.com/watch?v=giE4SuC9qWc
- Animats 7y agoOK, so this is depth estimation from a single image, right? Like this classic paper.[1] Then that's used to turn the image into a set of layers. This is often done for video; that's how 2D movies are turned into 3D movies. [1] http://www.cs.cornell.edu/~asaxena/learningdepth/ijcv_monocular3dreconstruction.pdf http://www.cs.cornell.edu/~asaxena/learningdepth/ijcv_monocu...
- sniklaus 7y agoMore or less. Estimating the depth from a single image is highly challenging and far from solved. We thus had to made sure that the depth estimate is suitable for synthesizing new views. And we are not explicitly modelling layers, we actually model the scene geometry as a point cloud. But you definitely got the gist of it. By the way, one advantage when estimating the scene geometry in a video is that it is possible to employ structure from motion.
- ChuckMcM 7y agoCan we replace that with http://sniklaus.com/papers/kenburns http://sniklaus.com/papers/kenburns the actual paper?
- sniklaus 7y agoI was thinking about what I should post and decided to make this little teaser since it demonstrates the gist of our work within a few seconds. I understand that the typically Hacker News audience may find the paper more worthwhile though.
- ChuckMcM 7y agoIt was a good thought, however the mechanism doesn't easily lend itself to following through to the paper. Rather than using a video consider a web page with your examples embedded that can be played, (even animated gifs would work) and a link to the paper. That gets you a bit of both worlds.
- sniklaus 7y agoGood suggestion, thank you!
- dilloooo 7y agoshut up and take my money.
- lostgame 7y agoIt’s been said, but this is mistitled - this is not a ‘Ken Burns’ effect, but rather a parallax panning effect with depth. To be honest it’s far more impressive than I expected.
- JansjoFromIkea 7y agoYep same here, it misrepresents and understates the actual thing to the point that I wouldn't have even clicked on it if the 3D part of the title didn't confuse me.
- nayuki 7y agoThis visual animation effect is almost the signature of the YouTuber "Business Casual": https://www.youtube.com/channel/UC_E4px0RST-qFwXLJWBav8Q/videos https://www.youtube.com/channel/UC_E4px0RST-qFwXLJWBav8Q/vid...
- sniklaus 7y agoIt seems like he is using them extensively but not too extreme. Looks great, thank you for sharing!
- dperfect 7y agoThe most interesting thing about this (compared to results from similar research/projects) is that in all of the examples, camera movement is forward and down relative to the original perspective. The results are really good, and some of that may be due to a superior algorithm, but it's also aided in large part by the choice of movement. Since objects lower in the frame tend to be closer (foreground elements), the downward camera movement causes those objects to occlude parts of the background above (and behind) them, meaning that a relatively small portion of the background needs to be inpainted by the algorithm. If too much is interpolated, visual artifacts often ruin the illusion. The forward movement also helps in this case as those foreground objects grow in size (relative to the background) with time, so there's even less need for interpolation. If the movement were primarily lateral (or reversed relative to the original image), I imagine the algorithm would have a much harder time producing good results [1]. EDIT: After skimming the paper, it appears that the algorithm is automatically choosing these best-case virtual camera movements: > This system provides a fully automatic solution where the start- and end-view of the virtual camera path are automatically determined so as to minimize the amount of disocclusion. That is pretty impressive. I had originally assumed the paths were cherry-picked by humans, so it's cool that the paths themselves are automatically chosen (and that the algorithm matches the intuitive best-case scenario in most cases). It's still slightly misleading in terms of results because they mention that user-defined movements can be used instead, but of course, the results are likely to suffer significantly if the movement doesn't match the optimal path chosen by the algorithm. [1] The last example shown in the full results video illustrates the issue with too much background interpolation in lateral movement: http://sniklaus.com/papers/kenburns-results http://sniklaus.com/papers/kenburns-results
- sniklaus 7y agoThank you for sharing your thoughts! We designed the automatic camera path estimation to minimize the amount of disocclusion which indeed simplifies the problem. As you correctly pointed out, inpainting the background is an additional challenge and while we address it, the inpainted results sometimes lack texture.
- astannard 7y agoAbsolutely love it, fantastic work!
- sprash 7y agoFound something similar on shadertoy [1] from 2013. Of course the geometry is handcoded in this case but it would be a good starting point to implement something like this via shaders in WebGL and use it for all your images on your Webpage. [1]: https://www.shadertoy.com/view/XdlGzH https://www.shadertoy.com/view/XdlGzH
- sniklaus 7y agoThat looks awesome, thank you for sharing!
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