Towards an Unequivocal Representation of Actions
원문 초록
This work introduces verb-only representations for actions and interactions; the problem of describing similar motions (e.g. 'open door', 'open cupboard'), and distinguish differing ones (e.g. 'open door' vs 'open bottle') using verb-only labels. Current approaches for action recognition neglect legitimate semantic ambiguities and class overlaps between verbs (Fig. 1), relying on the objects to disambiguate interactions. We deviate from single-verb labels and introduce a mapping between observations and multiple verb labels - in order to create an Unequivocal Representation of Actions. The new representation benefits from increased vocabulary and a soft assignment to an enriched space of verb labels. We learn these representations as multi-output regression, using a two-stream fusion CNN. The proposed approach outperforms conventional single-verb labels (also known as majority voting) on three egocentric datasets for both recognition and retrieval.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Including Semantic Information via Word Embeddings for Skeleton-based Action Recognition
A Review on Coarse to Fine-Grained Animal Action Recognition
Cross-Model Cross-Stream Learning for Self-Supervised Human Action Recognition
B2C-AFM: Bi-Directional Co-Temporal and Cross-Spatial Attention Fusion Model for Human Action Recognition
MMNet: A Model-Based Multimodal Network for Human Action Recognition in RGB-D Videos
InHARD - Industrial Human Action Recognition Dataset in the Context of Industrial Collaborative Robotics
토론
이 논문과 연결된 포럼 글이 아직 없습니다.