TVNet: Temporal Voting Network for Action Localization
원문 초록
We propose a Temporal Voting Network (TVNet) for action localization in untrimmed videos. This incorporates a novel Voting Evidence Module to locate temporal boundaries, more accurately, where temporal contextual evidence is accumulated to predict frame-level probabilities of start and end action boundaries. Our action-independent evidence module is incorporated within a pipeline to calculate confidence scores and action classes. We achieve an average mAP of 34.6% on ActivityNet-1.3, particularly outperforming previous methods with the highest IoU of 0.95. TVNet also achieves mAP of 56.0% when combined with PGCN and 59.1% with MUSES at 0.5 IoU on THUMOS14 and outperforms prior work at all thresholds. Our code is available at https://github.com/hanielwang/TVNet.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Zero-Shot Temporal Interaction Localization for Egocentric Videos
DeepConvContext: A Multi-Scale Approach to Timeseries Classification in Human Activity Recognition
Talk is Not Always Cheap: Promoting Wireless Sensing Models with Text Prompts
TimeLoc: A Unified End-to-End Framework for Precise Timestamp Localization in Long Videos
XRF V2: A Dataset for Action Summarization with Wi-Fi Signals, and IMUs in Phones, Watches, Earbuds, and Glasses
A Multimodal Dataset for Enhancing Industrial Task Monitoring and Engagement Prediction
토론
이 논문과 연결된 포럼 글이 아직 없습니다.