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Computer vision’s shifting methods, from CNNs to transformers

A user’s retrospective describes transformers as dominant and reinforcement learning as rising, and points to 2024 as the biggest shift in computer-vision tasks.

Kosta DerpanisKD
Sameh KhamisSK
2 Sources, 19d ago, first seen 19d ago

TLDR

Looking back on computer vision in a September 20, 2026 post, a user says convolutional neural networks (CNNs) “came out of nowhere,” while recurrent neural networks and generative adversarial networks “had their moment.” They describe transformers as dominant and reinforcement learning as rising. For tasks, they identify 2024 as the year of the biggest change, with segmentation “losing the throne.”

Combined views

1.1K

2 Sources, first seen 19d ago

11 likes1 comments3 saves3 reposts

Combined views

1.1K

2 Sources, first seen 19d ago

11 likes1 comments3 saves3 reposts

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Positive——Negative

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2 Sources

Sameh Khamis@sameh_khamisBack in my day moment! was curious to see how methods & tasks in computer vision evolved since I joined. CNNs came out of nowhere, RNNs / GANs had their moment, and now transformers dominate, RL rising. Tasks had their biggest change in 2024 with segmentation losing the throne.19d
Kosta Derpanis@CSProfKGDRT @sameh_khamis: Back in my day moment! was curious to see how methods & tasks in computer vision evolved since I joined. CNNs came out of…19d
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    2 Sources

    Sameh Khamis@sameh_khamisBack in my day moment! was curious to see how methods & tasks in computer vision evolved since I joined. CNNs came out of nowhere, RNNs / GANs had their moment, and now transformers dominate, RL rising. Tasks had their biggest change in 2024 with segmentation losing the throne.19d
    Kosta Derpanis@CSProfKGDRT @sameh_khamis: Back in my day moment! was curious to see how methods & tasks in computer vision evolved since I joined. CNNs came out of…19d
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