March 27, 2024, 4:46 a.m. | Jongha Kim, Jihwan Park, Jinyoung Park, Jinyoung Kim, Sehyung Kim, Hyunwoo J. Kim

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.17709v1 Announce Type: new
Abstract: Visual Relationship Detection (VRD) has seen significant advancements with Transformer-based architectures recently. However, we identify two key limitations in a conventional label assignment for training Transformer-based VRD models, which is a process of mapping a ground-truth (GT) to a prediction. Under the conventional assignment, an unspecialized query is trained since a query is expected to detect every relation, which makes it difficult for a query to specialize in specific relations. Furthermore, a query is also …

arxiv cs.cv detection quality query relationship transformer type visual

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