本文将attention加入了action recognition中了,属于比较早的文章,思路较简单,但其中的一些想法还是很有启发性的。 Attention: Attention的思想是将目标作进一步refined,让模型可以捕获更精细的特征,是通过将特征分成更小的patch,Attention将筛选出更有利于描述特征的那部分patch。 分为soft-attention和hard-attention两种。
但是,我们发现Adam通常会在3个epochs后收敛。 我们的实现基于Theano(Bastien等人,2012)处理梯度的计算,代码如下:https://github.com/kracwarlock/action-recognition-visual-attention。 对于训练和测试,我们的模型以固定的fps速率一次采样30帧。从第一帧开始,我们将每个视频分成30帧的组,fps速率选择30帧,然后以1的步...
Attention in CV attentionmodeling for OCR in the wild.6 Recursive是结构上的循环(节省空间增加深度,类似与ISTN),recurrent是时间上的循环(多层使关注不同任务...1.Attentionin CV 1.1. CHAM:actionrecognitionusingconvolutional hierarchicalattentionmodel.5 ...
Darrell, "Long-term recurrent convolutional networks for visual recognition and description," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 2625-2624. [5] S. Sharma, R. Kiros, and R. Salakhutdinov, "Action recognition using visual attention," arXiv...
Human action recognitionReinforcement learningVisual attentionHuman action recognition in videos is a challenging and significant task with a broad range of applications. The advantage of the visual attention mechanism is that it can effectively reduce noise......
Action Recognition Using Visual Attention with Reinforcement Learning Human action recognition in videos is a challenging and significant task with a broad range of applications. The advantage of the visual attention mechanis... H Li,J Chen,R Hu,... - International Conference on Multimedia Modeling...
Action Recognition using Visual Attention [ PDF | BibTeX | Poster ] Shikhar Sharma, Ryan Kiros, Ruslan Salakhutdinov NIPS Time Series Workshop, 2015 Related PublicationAction Recognition and Video Description using Visual Attention [ PDF | BibTeX ] Shikhar Sharma Masters Thesis, University of ...
Action Recognition using Visual Attention We propose a soft attention based model for the task of action recognition in videos. We use multi-layered Recurrent Neural Networks (RNNs) with Long-Short Term Memory (LSTM) units which are deep both spatially and temporally. Our model learns to focus...
action-recognition-visual-attention, 基于软注意的深层递归神经网络动作识别 基于视觉注意的动作识别基于软注意的视频动作识别任务模型。 我们采用多层次递归神经网络( RNNs ),具有长期内存( LSTM ) 单元和时间和时间。 我们的模型学习在视频框架中有选择地集中注意力,并在几个视频中分类视频。 模型本质上了...
S.: CBAM: Convolutional Block Attention Module. In: Proceedings of European Conference on Computer Vision (2018) Sharma, S., Kiros, R., Salakhutdinov, R.: Action recognition using visual attention. In: Computer Science (2015) Kim, D. , Cho, D. , Kweon, I. S.: Self-supervised video ...