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Yanqi Li

2 accepted papers

2026

From Scene to Object: Enhancing Open-Vocabulary Object Detection via Foreground-Background Context Reasoning

AAAI 2026technical

Open-Vocabulary Object Detection (OVOD) aims to detect both known and novel categories in complex visual scenes, surpassing the limitations of conventional closed-set detectors. Recent advances in vision-language models (VLMs) like CLIP have enabled zero-shot recognition by aligning visual features

Cited by 0SourcePDFScholar
2025

Benefit From Seen: Enhancing Open-Vocabulary Object Detection by Bridging Visual and Textual Co-Occurrence Knowledge

ICCV 2025poster

Open-Vocabulary Object Detection (OVOD) aims to localize and recognize objects from both known and novel categories. However, existing methods rely heavily on internal knowledge from Vision-Language Models (VLMs), restricting their generalization to unseen categories due to limited contextual unders…

Cited by 0SourcePDFScholar