Determined by User Needs: A Salient Object Detection Rationale Beyond Conventional Visual Stimuli
Chenglizhao Chen, Shujian Zhang, Luming Li, Wenfeng Song, Shuai Li

TL;DR
This paper introduces UserSOD, a new salient object detection task that emphasizes detecting objects aligned with user needs, addressing limitations of traditional stimulus-based methods.
Contribution
It proposes the UserSOD task focusing on user needs in salient object detection and highlights the need for dedicated datasets.
Findings
Identifies the gap in existing SOD methods regarding user needs.
Advocates for a new task, UserSOD, to align detection with user needs.
Highlights the lack of datasets for training and testing UserSOD.
Abstract
Existing \textbf{s}alient \textbf{o}bject \textbf{d}etection (SOD) methods adopt a \textbf{passive} visual stimulus-based rationale--objects with the strongest visual stimuli are perceived as the user's primary focus (i.e., salient objects). They ignore the decisive role of users' \textbf{proactive needs} in segmenting salient objects--if a user has a need before seeing an image, the user's salient objects align with their needs, e.g., if a user's need is ``white apple'', when this user sees an image, the user's primary focus is on the ``white apple'' or ``the most white apple-like'' objects in the image. Such an oversight not only \textbf{fails to satisfy users}, but also \textbf{limits the development of downstream tasks}. For instance, in salient object ranking tasks, focusing solely on visual stimuli-based salient objects is insufficient for conducting an analysis of fine-grained…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
