A Semantic-Retrieval-Augmented Detector (SRA-Det) is proposed that uses an attention-based module to retrieve multiple semantic facets from token-level text features, and a soft-min matching rule that behaves like a differentiable logical AND over these facets, ensuring that all key attributes are satisfied.
Experimental results show that the proposed open-vocabulary object detection framework performs excellently on multiple benchmark datasets such as LVIS and COCO-O, demonstrating stronger adaptability to complex scenarios.
Tao Liu, Chongwen Wang· International Conference on...· 0 citations
OVIP-SG is presented, a unified framework for instance-preserving semantic mapping, functional scene partitioning, and language-guided small, fine-grained object retrieval that outperforms ConceptGraphs under a unified evaluation protocol on Replica.
Tianjing Hao, Hai-Yu Lan, Ang Li et al.· 0 citations
Experiments demonstrate that VocaDet achieves effective open-vocabulary detection performance without conventional detector training, while supporting continuously expandable recognition capability as additional positive and negative samples are accumulated.
Open-vocabulary object detection leverages vision-language pre-training to achieve cross-category generalization. With the progressive refinement of models such as GLIP, Grounding DINO, and YOLO-World, detectors have exhibited substantially enhanced zero-shot recognition capabilities on open vocabularies, with YOLO-Wor...
Recent unified open-vocabulary detection (OVD) supports heterogeneous prompts, including text queries, visual exemplars, and their combinations, but often rely on increasingly complex designs such as heavy cross-modal fusion, staged training, and iterative annotation pipelines. We revisit whether such complexity is nec...
Xiao-Yan Wei, Zhi-Min Yao, Rui-Lin Yang et al.· 0 citations
FSG-AID is presented, which integrates fine-grained semantic guidance with an attribute-aware iterative decoder and jointly exploits visual and language features to mine attribute semantics, initialize the target query, and iteratively refine the target representation.
Xiya Bu, Yu Liu, Jizhe Yu et al.· Multimedia Systems· 0 citations
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