99 citations · 279 across the 37 of their papers we have counts for
4 papers · 1 filter
More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal Aggregation
Quanfu Fan, Chun-Fu Chen, Hilde Kuehne +2
Current state-of-the-art models for video action recognition are mostly based on expensive 3D ConvNets. This results in a need for large GPU clusters to train and evaluate such arc…
A Hybrid RNN-HMM Approach for Weakly Supervised Temporal Action Segmentation
Hilde Kuehne, Alexander Richard, Juergen Gall
Action recognition has become a rapidly developing research field within the last decade. But with the increasing demand for large scale data, the need of hand annotated data for t…
Mining YouTube - A dataset for learning fine-grained action concepts from webly supervised video data
Hilde Kuehne, Ahsan Iqbal, Alexander Richard +1
Action recognition is so far mainly focusing on the problem of classification of hand selected preclipped actions and reaching impressive results in this field. But with the perfor…
Unsupervised learning of action classes with continuous temporal embedding
Anna Kukleva, Hilde Kuehne, Fadime Sener +1
The task of temporally detecting and segmenting actions in untrimmed videos has seen an increased attention recently. One problem in this context arises from the need to define and…