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#video understanding

4 results
cs.CV2019

Adversarial Seeded Sequence Growing for Weakly-Supervised Temporal Action Localization

Chengwei Zhang, Yunlu Xu, Zhanzhan Cheng +4

The paper proposes a weakly‑supervised framework for temporal action localization that alternates between a Seeded Sequence Growing network, which expands reliable seed regions, an…

#weakly-supervised learning#temporal action localization#adversarial training#seeded sequence growing
cs.CV2019

Learning Visual Actions Using Multiple Verb-Only Labels

Michael Wray, Dima Damen

The paper proposes using multiple verb-only labels for video action recognition and cross‑modal retrieval, learning these labels via regression to capture semantic ambiguities and…

#action recognition#video understanding#multi‑label learning#verb semantics
cs.CV2019

Multi-Granularity Fusion Network for Proposal and Activity Localization: Submission to ActivityNet Challenge 2019 Task 1 and Task 2

Haisheng Su, Xu Zhao, Shuming Liu

The paper introduces a Multi-Granularity Fusion Network that merges proposals from various top‑down and bottom‑up frameworks to improve temporal action proposal generation and loca…

#temporal action proposal#action localization#multi-granularity fusion#video understanding
cs.CV2019

Submission to ActivityNet Challenge 2019: Task B Spatio-temporal Action Localization

Chunfei Ma, Joonhyang Choi, Byeongwon Lee +1

The paper describes an end‑to‑end RGB‑only system for spatio‑temporal action localization in videos, built on SlowFast networks and enhanced with correlation‑preserving data augmen…

#spatio-temporal action localization#video understanding#slowfast network#data augmentation