187 citations · 261 across the 8 of their papers we have counts for
5 papers · 1 filter
Weakly Supervised Cascaded Convolutional Networks
Ali Diba, Vivek Sharma, Ali Pazandeh +2
Object detection is a challenging task in visual understanding domain, and even more so if the supervision is to be weak. Recently, few efforts to handle the task without expensive…
Deep Temporal Linear Encoding Networks
Ali Diba, Vivek Sharma, Luc Van Gool
The CNN-encoding of features from entire videos for the representation of human actions has rarely been addressed. Instead, CNN work has focused on approaches to fuse spatial and t…
Efficient Two-Stream Motion and Appearance 3D CNNs for Video Classification
Ali Diba, Ali Mohammad Pazandeh, Luc Van Gool
The video and action classification have extremely evolved by deep neural networks specially with two stream CNN using RGB and optical flow as inputs and they present outstanding p…
DeepCAMP: Deep Convolutional Action & Attribute Mid-Level Patterns
Ali Diba, Ali Mohammad Pazandeh, Hamed Pirsiavash +1
The recognition of human actions and the determination of human attributes are two tasks that call for fine-grained classification. Indeed, often rather small and inconspicuous obj…
DeepProposals: Hunting Objects and Actions by Cascading Deep Convolutional Layers
Amir Ghodrati, Ali Diba, Marco Pedersoli +2
In this paper, a new method for generating object and action proposals in images and videos is proposed. It builds on activations of different convolutional layers of a pretrained…