most citedVideoLSTM Convolves, Attends and Flows for Action Recognition

64 citations · 91 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV20173 cited

Examining Cooperation in Visual Dialog Models

Mircea Mironenco, Dana Kianfar, Ke Tran +2

In this work we propose a blackbox intervention method for visual dialog models, with the aim of assessing the contribution of individual linguistic or visual components. Concretel…

cs.CV201713 cited

Tracking for Half an Hour

Ran Tao, Efstratios Gavves, Arnold W. M. Smeulders

Long-term tracking requires extreme stability to the multitude of model updates and robustness to the disappearance and loss of the target as such will inevitably happen. For motiv…

cs.NE201711 cited

Temporally Efficient Deep Learning with Spikes

Peter O'Connor, Efstratios Gavves, Max Welling

The vast majority of natural sensory data is temporally redundant. Video frames or audio samples which are sampled at nearby points in time tend to have similar values. Typically,…

cs.CV2017

Unified Embedding and Metric Learning for Zero-Exemplar Event Detection

Noureldien Hussein, Efstratios Gavves, Arnold W. M. Smeulders

Event detection in unconstrained videos is conceived as a content-based video retrieval with two modalities: textual and visual. Given a text describing a novel event, the goal is…

cs.CV201664 cited

VideoLSTM Convolves, Attends and Flows for Action Recognition

Zhenyang Li, Efstratios Gavves, Mihir Jain +1

We present a new architecture for end-to-end sequence learning of actions in video, we call VideoLSTM. Rather than adapting the video to the peculiarities of established recurrent…

cs.CV2016

Siamese Instance Search for Tracking

Ran Tao, Efstratios Gavves, Arnold W. M. Smeulders

In this paper we present a tracker, which is radically different from state-of-the-art trackers: we apply no model updating, no occlusion detection, no combination of trackers, no…