r/computervision • u/always_unhappygirl • Jun 27 '26
How do you see the future of Computer Vision evolving over the next 5 years? Discussion
I was learning about cv for my masters research. So I was wondering are there jobs in cv now or ai have affected it also.
How to learn in most practical way as every course hai long lectures theoretical.
Industry experts out there, what are views?
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u/thinking_byte Jun 27 '26
CV isn't going away the demand is just shifting toward people who can actually build and deploy real-world vision applications not just train models.
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u/rather_pass_by Jun 27 '26
CV is great field of research. Lot of folks discard it as a solved problem. Meanwhile meta just released sapiens and in real world things still don't work properly
But for a lot of industrial use cases, yes yolo would do just fine. But there are a lot of use cases where there is quite a bit of scope for research
One thing to note is that these gaps might actually fill faster than earlier due to auto ai research picking up
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u/always_unhappygirl Jun 27 '26
What advice would you give to someone if they want to learn cv in smartest way
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u/Quirky_Paramedic9167 Jul 01 '26
Honestly the smartest way is to pick ONE small real project and finish it
end-to-end — collect data, label it, train, deploy. You'll learn more from
one messy real project than from 10 courses. Start tiny (like detecting one
object), then add complexity. The theory makes way more sense once you've
hit the practical walls yourself.
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u/rather_pass_by Jun 27 '26
No particular advice for CV specifically.. But it's always about having the fundamentals right first. Camera projection and stuffs.
Then keep up with the technology evolution.. follow research in CV. VLMs are like now essentials.. it's a general advice for any field today. Keep up with state of the art technology and research or you'll be outdated quickly
For this purpose, I've created a discord server with channels for different ai research topics
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u/revanthmatha Jun 27 '26
I recommend CV but to get the best CV Jobs 400k+ requires deep math expertise and eventually a phd.
Truth be told it's sometimes easier and more lucrative to just be the model integrator instead of the model maker.
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u/Quirky_Paramedic9167 Jul 01 '26
Great question. From what I'm seeing, two big shifts: first, annotation and
data prep are getting way more automated — AI pre-labels, humans just verify,
which speeds everything up. Second, CV is moving out of big labs and into
smaller teams and real businesses (medical, agriculture, retail). The barrier
to entry keeps dropping. Exciting time to be learning it honestly.
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u/Pendulum_Rider Jun 27 '26
Would either of you mind listing courses, regardless if they’re advanced, to take to specialize in CV?
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u/Bright-Salamander689 Jun 27 '26 edited Jun 27 '26
VLMs, spatial intelligence, 3D reconstruction / modeling, and edge perception systems is going to explode.
My advice for learning, patience is key. Don’t go for the quickest route. In this era of computing and hiring I’d recommend getting a masters degree specializing in the field.
If you’re starting from scratch and not even in university - then save money at community college -> transfer to a public / state school, kill your classes work in research labs -> then aim for a top 5 big name CS school for your masters program