Computer Vision AI

Computer vision AI failures — image and vision-model mistakes in agentic systems

43 patterns

Computer vision AI failures — image and vision-model mistakes in agentic systems. We've tracked 43 distinct Computer Vision AI patterns across production AI agent deployments — most commonly in Vision and Images systems. One recurring example: 3D Reasoning Collapse — Model Cannot Reason About 3D Structure from Single 2D Image

Each pattern below documents the specific failure mode, why it happens, and how teams have mitigated it in practice — use this page as a reference when building guardrails, writing evals, or debugging an agent that's already misbehaving in this way.

AI Agent Perspective Blindness: Causes and Fixes

Frequency:Common
Category:Vision and Images

A vision model recognizes objects from frontal views but fails on the same objects rotated, tilted, or viewed from unusual angles. Training data skews heavily toward canonical frontal views, so accuracy drops sharply — sometimes by more than half — the further an object's actual orientation strays from that norm.

Perspective Distortion Misunderstanding

Frequency:Common
Category:Vision and Images

Vision models misinterpret perspective distortion; assume objects are deformed when they're actually normally-shaped but viewed from non-frontal angles; or fail to account for perspective when estimating actual object dimensions