this is the best thing that has happened during the pandemic. I teach seam carving as a PhD student, but now I feel useless :D

Combine a few simple algorithms - in this case edge detection and minimum energy path search - and what you get is pure black magic. That is why I love computer science!

"It picks up on the edginess of Mario" --- Grant Sanderson 2020

People waste time on Netflix when you have Grant around. Crazy.

MIT are lucky to have you!

I have my own classes, but I’m watching this series as well for Grant.

If you can, please do more of these computer science applied math on the main channel. They are really interesting, and way easier to remember thanks to your way of explaining. Also seeing your face while explaining, like you do here, I think it's better then just having the graphics full screen

How can he be very good at storytelling this kind of complicated and multilayered concepts/techniques. A genius.

Grant's lectures are always pure gold. We need to keep the activities in the comments so the KZfaq algorithms bless this video. It will help spread knowledge and will definitely make the world a better place.

i love the dynamic programming example.. changin from exponential order to multiplication just by reversing the way we do computation.. that is absolutely awesome..

in this episode grant teaches us how to optimally get over your ex

This is the best explanation of magic of content aware shrinking. Thank you! Спасибо!

Great presentation, Grant! So clear and concise, despite the depth. Makes it look easy and natural. Really good!

Grant you're great

Wow I've never seen anyone to explain dynamic programming simpler!

Isn't the idea of using a seam at every step itself a greedy algorithm? Just based on my intuition, it should be possible to carve a seam that makes other future seams significantly less optimal, perhaps by cutting half of a seam that could be a future option. Of course, the greedy algorithm seems to work well enough, but perhaps there's a DP approach that could let us choose better seams by looking into potential future seams.

That was so cool.

This is just amazing! Grant not only knows a lot but explains in a way that makes it very simple

Nice video. Here's an alternative justification of three rows in the Sobel filter. 1) taking a derivation requires at least two points per output, so the dimension of the convolution will be one less. 2) if you want a gradient matrix, each slice (partial derivative) should be the same size so you need to average neigboring pixels in every other dimension. 3) if you average the derivativesto reduce noise, you should also average the (averaged) dimensions for the same reasons above. This gives you the vertical weights of [1; 2; 1].

I live in germany and im only in 10th grade but i still really enjoy watching these videos

This must be grants lowest views but thanks a lot for putting such content and making it accessible

Everything about this video is great

That's why I love algorithms, they are made by most genuine persons.

Brilliant explanation of a brilliant concept 😮

This is awesome, thanks. Especially the bit at the end - great potential for mischief!

Getting rid of Ex's feature was just hilarious

What a simple clever algorithm. That should be on every photo editting tools

Using dynamic programming to make lockscreen wallpapers would also be an apt title. I loved the teal gradients in starry night ❤️

These lectures are amazing. Thank you

I wish I teach as well as Grant. Right now I'm blaming it on my lack of time to prepare as I teach online as a side job. But really, even if I have more time, the bar he sets is pretty high.

This guy sounds really similar to the talking pi at 3blue1brown

Just had a crazy idea!! What if you could use this same concept to slow down a music file without distorting it?? That is a puzzle that I don't think we've solved yet!

Grant is a teaching genius.

Instead of wasting my time watching a netflix show, I enjoyed learning about a fun way to make use of a triangle

So, is this a good summary of what we are doing? 1. Convolve the image with a sobel kernel (vertical or horizontal), which contains some negative values 2. The resulting RGB object may have negative values in red, green, and/or blue channels 3. Take the L1 norm of each pixel (adding the absolute values of three color components), obtaining a non-negative number, possibly greater than 1 4. Repeat the same procedure with the other sobel kernel (horizontal or vertical) 5. Take the L2 norm of the two sobel results

Fascinating

There is also a cool looking glitch effect when you just remove N pixels with minimal entropy in each row without connection them in path

i was like "hold on this guy sounds familiar" and then it clicked

Why do we need to go only bottom to top? How does the algorithm care if we go from top to bottom in cumulative addition? Also, what if we want to reduce the image so as to keep the aspect ratio constant? Shouldn't we have two cumulative addition images one for top to bottom and another for left to right? If it's a 16:9 image, do we need to cut out top-bottom 16 times and then left-right 9 times and repeat?

Look at that fresh cut. Damn Grant.

"The great and one and only" Uh oh

Wow , pretty like the exercises on Dynamic Programming in Introducton To Algorithms...

So good 🎉

This is such incredibly good content, if the universities don't pick up their slack soon, youtube will just demolish them.

Wow, this is great explanation of these algorithms, really awesome. Also, you managed to utter "picks up on the edginess of Mario", which wins the internet today.

thank you

At 22:48 why are we adding j==1 to dir while saving min item indices

Awesome

Talking in terms of energy it looks like a thunderbolt going down through the path of least energy :D It could be called the thunderbolt algorithm.

This is awesome. Thank you!

just awesome explanation...!!!

go grant go!

Does solving the sub problems from top to bottom rather than from bottom top,would it give the same shortest energy path?

Thank you

i translated your code in Python! it is great!!

wonderful lecture!!

15:00 but dijkstra is faster, no?

THIS IS SO DOPE!!!!!! thanks grant! cool hair too!

Edgy Mario looks like he's going through an emo phase.

does anyone know where can I find the "original paper" he is referring to at 02:50?

billions of people are busy watching despacito and only handful of thousand people are watching this interesting video. explains why the world is stupid.

Has there been any study of seam carving with horizontal directions instead of just downward?

Can you parallel this with the concept of value functions from reinforcement learning/marcov decision processes?

I got a question: do you re-compute energies after each seam removal?

Didn't know it was you Grant :)

Gold mine

Grant so handsome, lecture so amazing, using my whole attention to learn this material! Thanks~

Quality!

No link to the notebook ?

After removing a seam, is it best to recalculate the energy values or to continue using the original ones?

Where can I get started learning Julia?

Great video! Quick question: your seams go top-to-bottom (for horizontal resizing), so why use √(vx²+vy²) instead of just |vx|, that is, only convolving with sx?

Which programming did Grant used there not looks like python but almost similar to it.

Oh I missed the live class!

12:56

or a toilet brush to clean all of that yest thats been accumulating for years in the khukhus

Why hasn't this been used more as a preprocessing step for deep learning models?

This feature is alredy implemented in photoshop works both ways

It's the meme algorithm

Anyone catch the title of the seam-carving paper?

I wonder what the results would be if you used some Machine Learning attention activation (like a GAM) instead of a simple edge detection. Maybe it could "understand" the important regions and perform better.

Is this a some kind of magic?🤏

what programming language is he using?

Just one question. After eliminating one steam? We have to recalculate everything again? Because of steam pixel overlap.

Content aware scaaaaaalle

Cool！

26:54 Creepy, he’s still holding the hand of his vanished ex-girl friend!

Is the full course getting uploaded?

What is the animations software?

Photoshop can do it perfectly well. It’s called content preserving scaling

Where do I know his voice from?

I'm not a programmer but seam duplication with interpolation should also be easily doable?

Other profs: 200 views Grant: 1.6k views

I mean, isn't this already a thing anyway? Content Aware Scaling

But why did Julia drop OpenCL support?

Is he the 3b1b guy?

LOVE GRANT LOVE GRANT LOVE GRANT LOVE GRANT I AM DEEPLY DEPRESSED THAT HE WILL DIE

You're 3Blue1Brown change my mind.

Is this Loopop lol

no squish? lol look at that pomegranate