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arXiv AI By Jirong Zha, Yanwei Liao, Yemin Wang, Xiangmin Yi, Siqi Peng, Yingfeng Chen, Chen Gao, Xinlei Chen

Task-Utility IQA: Rethinking Image Quality Assessment in Embodied Tasks

Read the original on arXiv AI →

The paper proposes rethinking image quality assessment (IQA) for embodied tasks by moving from generic score regression to goal‑conditioned judgments based on task utility. It introduces an MLLM‑based IQA agent that reasons about task requirements, grounds quality evidence, and outputs decision‑facing assessments. Experiments on VisDrone show that conventional perceptual metrics and generic IQA scores poorly predict downstream VLM task success, whereas a task‑conditioned utility score better indicates whether visual input supports the target task.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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