Computer Vision Interview Questions, issue 10, Jan 11, 2026

The Early vs Slow Fusion Trap

Computer Vision Engineer interview at Meta, and the interviewer asks:

β€œWe’re debating between 𝘌𝘒𝘳𝘭𝘺 𝘍𝘢𝘴π˜ͺ𝘰𝘯 and 𝘚𝘭𝘰𝘸 𝘍𝘢𝘴π˜ͺ𝘰𝘯 for our new video understanding model. Everyone knows 𝘚𝘭𝘰𝘸 𝘍𝘢𝘴π˜ͺ𝘰𝘯 captures motion better, but what is the specific computational consequence of maintaining that temporal dimension through multiple layers that kills our training budget?”

Don’t say: β€œπ˜šπ˜­π˜°π˜Έ 𝘍𝘢𝘴π˜ͺ𝘰𝘯 is slower because 3D convolutions are just more complex than 2D convolutions.”

The hidden activation-memory cost of keeping time alive in deep video networks.

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