1:10:10 “can we give a computer one picture and outcomes a description like this… you give the computer one picture - it gives you one sentence… we are not here yet”. This is 2016, and Dr. Fei-Fei Li cannot envision even in her wildest dreams that a few years later, we shall not only overcome this problem but solve the opposite - give a computer a sentence, and it shall create a picture. She was too ‘shy’ to even ask a computer to do such a thing. What is this something that we don’t even dare to ask a computer to do today, but in 2028 computers will do? 😊
It's really eazy to understand Feifei Li's accent, and good lectures, I'll try my best to grasp the knowledge. Dream being a Stanford CS student one day...
Just want to say a big Thank you, this course had helped me prepare the foundation for my PhD back in 2017. Literally watched it multiple times to internalise the concepts
An absolutely beautiful class. Everything is getting closer to abstraction in education, such as math that you learn formulas but don't know where did they come from, or why should you use it. That's a necessary class to computer vision in terms of modern education, people shouldn't learn algorithms, architectures ml frameworks before understanding where did this come from, through our evolution and years of analysis and construction of what we call today modern computer vision
I have attended the CS21n last year (2015 session). In the 2016 session, some cutting edge techs and applications are added such as image caption. They also provide videos! Thus, I am planning to go though it again~!
Great intro! , the whole picture of Computer Vision summarized. But I have some thought about making a computer write an essay, the inner imprecision of language pointed out by Wittgenstein for instance. Any discussion forum you may recommend?
![[1hr Talk] Intro to Large Language Models](http://i.ytimg.com/vi/zjkBMFhNj_g/mqdefault.jpg)
In case anybody is interested, the photo with the river and houses on slide 42 (at abuot 1:15:08) is from the city of Tübingen in Germany.
*My takeaways:*
1. Agenda of this lecture 11:41
2. A brief history of computer vision 13:45
3. Overview of this course series 57:50
1:10:10 “can we give a computer one picture and outcomes a description like this… you give the computer one picture - it gives you one sentence… we are not here yet”. This is 2016, and Dr. Fei-Fei Li cannot envision even in her wildest dreams that a few years later, we shall not only overcome this problem but solve the opposite - give a computer a sentence, and it shall create a picture. She was too ‘shy’ to even ask a computer to do such a thing. What is this something that we don’t even dare to ask a computer to do today, but in 2028 computers will do? 😊
So true!
It's really eazy to understand Feifei Li's accent, and good lectures, I'll try my best to grasp the knowledge. Dream being a Stanford CS student one day...
Just want to say a big Thank you, this course had helped me prepare the foundation for my PhD back in 2017. Literally watched it multiple times to internalise the concepts
Thank you so much for uploading this. I would really love if the cs231a could also be viewed online
What a great professor! Wish I could attend the lectures in person.
You should be grateful that you can attend the lectures at all. Virtual or otherwise.
She said that she is giving @Andrej a challenge and ChatGPT4 did the same thing in the 14 March 2023 release .
Thanks to this lecture i finally understand the basis of Deep Learning !
Great Professor
Cool
How much time you had to put in?
Always loved to hear Dr Fei Fei Li speaks even though this is nearly 10 years ago and she is still pretty hilarious.
An absolutely beautiful class. Everything is getting closer to abstraction in education, such as math that you learn formulas but don't know where did they come from, or why should you use it. That's a necessary class to computer vision in terms of modern education, people shouldn't learn algorithms, architectures ml frameworks before understanding where did this come from, through our evolution and years of analysis and construction of what we call today modern computer vision
Started my journey and watching this course now. Couldn't attend Stanford University but still good to be in the class in 2024 : )
Thank you so much for taking the videos and making this public!!
I have attended the CS21n last year (2015 session). In the 2016 session, some cutting edge techs and applications are added such as image caption. They also provide videos! Thus, I am planning to go though it again~!
Small world!
A ha, nice to meet you here, Doc Gu. Happy learning! I am busy with my paper recently and I haven't watched these videos yet.
She is amazing ! please don't delete CS231n courses
哈喽美女🌹
Thanks for posting, Good luck teaching this quarter!
So great! Chinese subtitles are so nice and precise.
This is great introduction subject computer science. Launches us to see some more amazing topic by Andrej
Awesome mates! Thanks for sharing this class with the rest of us :D Much appreciation and thanks!
感谢,没想到还能看到这么好的视频!
OMG Chinese subtitles!! Thanks for great lecture and work!
Amazing,
What a wonderful course! Only 665 views by now? I will share it with my friends.
You have a lot of friends, since the number of views is more than 220k :)
醍醐灌顶的入门视频，感谢
a convolution is like a retort and therefore inseparable from an edge work
Thank you very much for sharing this course, Andrej! Looks very cool and promising!
Thanks for posting and also not only in a legacy resolution.
Thanks for giving a chance to learn this wonderful course.
Great first lecture, so excited to get started!
I can learn more with the video,thanks
Thank you so much for sharing this, an invaluable resource.
Thanks for posting such great lectures. Good job!
感谢提供那么好的学习资源！！！
Thanks for posting! This course is awesome
Interesting and though-provoking introduction of CV!
Awesome! Hope to see more video lectures.
that was great, big thnx/ looking forward to the next steps
Hats off Professor !
Really enjoyed the introduction class.
thanks for recording this great course!! it's fun and interesting topic!!
Recommendable! E.g. A very high level introduction to the history of computer vision
Thank you so much! The course I think will actually improve my understanding on CNN for Vision
What an amazing lecture. Thanks a lot for posting this :)
A very good introduction to CNN
Great introduction to deep learning
Great lecture! Thanks for sharing. Watching from Australia :)
Chinese Subtitles !!!! F**king Awesome!!!
really nice course for beginners
Great course, Thanks for sharing!
Great intro! , the whole picture of Computer Vision summarized. But I have some thought about making a computer write an essay, the inner imprecision of language pointed out by Wittgenstein for instance. Any discussion forum you may recommend?
start to learn 加油！
Thank you andrej.Do you have video lectures cs231a visual network lectures.
So nice ,thanks for share this video :)
540 millions of evolution? where did You get that number?
where to find CS131 and CS231a?
I wonder if this lecture already needs an update?
I want to see the latest lectures in 2018, but i am not a Stanford student,very upset.
Great lecture!
来晚了，非常好的课程
Are the slides available on the cs231n course website or somewhere else?
I'd like to download it if it's available.
Thanks for uploading anyway.
Yes, they are available on the course website.cs231n.stanford.edu/2016/syllabus
Ah! Thanks.
Fei-Fei! Great course!!
Fantastic!
Thank you! this is amazing.
Great professor
Make my life easier since I don't need read fancy papers.
What are pre requisite for this course
居然有中文字幕，还不是自动识别的，真的太感动了...
plus 太感谢了 ！
太感谢了，有中文字幕
Where the cats okay??
1.25X speed is highly recommended :)
!!!! Chinese Subtitles!!! Happyyyyyyyyy!!!
Very small images!
Thank you so much!
It's a good opportunity to study CNN
啊啊啊，感谢。
*7 late days?!* GoDdEsS.
Thanks
Neural Networks not your Networks ... the subtitles..........
Fei Fei Li has an attractive accent.
Perfect course but I cannot understand all of the contents cause I cannot listen English well.
Where are you from?>
28:05
done
and this is the 100th
*Full solutions for Spring 2017 Assignments*
Check 'em out!
github.com/MahanFathi/CS231
Hall Gary Allen Paul Young Brenda
this is the 99th comment
废话一大堆
too many "ah ah ah", "you know" "all right?" "en en en en...". Please change your speaking style. The content is ok.
are you for real, bethankful of this amazing content for free. Entitled fucker.
Stfu you are just an idiot
41:47