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New benchmark WebEye tackles visual perception with external data

Researchers have introduced a new benchmark and framework called WebEye to address the challenge of visual perception in open-world scenarios. This benchmark focuses on tasks where identifying an object requires external information, such as recent events or multi-hop relations, before it can be localized within an image. The proposed Pixel-Searcher agentic workflow aims to resolve hidden target identities and bind them to visual instances, demonstrating strong performance on the WebEye benchmark. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Introduces a new benchmark and agentic workflow for visual perception, potentially advancing research in open-world object identification and grounding.

RANK_REASON Academic paper introducing a new benchmark and framework for visual perception. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

COVERAGE [1]

  1. arXiv cs.CV TIER_1 · Xiangyu Yue ·

    From Web to Pixels: Bringing Agentic Search into Visual Perception

    Visual perception connects high-level semantic understanding to pixel-level perception, but most existing settings assume that the decisive evidence for identifying a target is already in the image or frozen model knowledge. We study a more practical yet harder open-world case wh…