Check out the original SIGGRAPH presentation on it. There are lots of really great demos. It's one thing to read about the algorithm, but to see it in action is magical.

https://www.youtube.com/watch?v=6NcIJXTlugc

This is still amazing all of these years later.

I have a photo of my friend, his ex-wife and a few others standing together on a camping trip. I wanted to share that photo with the group since it was the tenth anniversary of that trip, but didn't want to remind my friend of his divorce, so I used seam carving to elide his ex-wife. (The tool I used allows you to paint areas of low or high energy.) The result was almost seamless (pun intended) and you wouldn't notice anything amiss if you weren't looking for it.

I think as a photo editing tool. The neatest nontrivial use i know is to “delete” objects. You can use segmentation algo to highlight an object and set its energy to 0 then seam carve out “naturally”.

I used seam carving in a side-project Chrome extension I developed [1]. The extension pull the top landscape photo from r/EarthPorn and resizes it to 1920x1080 using the seam carving library caire [2]. Then it uploads the resized image to Imgur where it can be used as the user's new tab wallpaper.

Perhaps using seam carving was a little bit overboard but I thought it would be interesting and it works really well for most Earth landscape photos. I only rarely see artifacts and minor distortions in the resized images it produces. Also since I only needed to resize one photo per day, the computational overhead was not a very big deal.

[1] https://github.com/micahcantor/dailypapers

[2] https://github.com/esimov/caire

It’s...not as useful as it first appears. It’s actually very computationally expensive to solve the mapping, and it can add quite of bit of space to the image to pre-compute the seam order (which is the proposal made by the original paper).

Each pixel can be tagged with a rank according to its seam number along each axis. If you have 4,000x4,000 pixels then each pixel needs a 12-bit integer value for each axis; and if you want the optimal map it’s another 1 bit per pixel. So something on the order of an extra 25-bits per pixel for a naive encoding, which almost doubles the size of an 8-bit per channel image.

It also has no explicit scene awareness. The energy function essentially defines an implicit heuristic of scene importance, which is surprisingly reasonable until you’re removing >25% of pixels along either axis.

I believe it shipped with Photoshop for a couple years (maybe still?) but in my experience it’s a bit more of an artistic effect than an automatic and scalable solution—and it would be really hard to make it run in real time at game frame rates. (I think the artifacts alone would make it not worth it for games.)

A non-practical application is for funny memes. Someone figured out Photoshop's Content Aware Scaling feature can hilariously distort faces [1], and people have been using it memes since.

My current favorite: https://www.youtube.com/watch?v=NRB_ASog9QU

[1] https://knowyourmeme.com/memes/content-aware-scaling