Deep video hashing (DVH) is a very appealing way to decrease storage costs and query times. In this work we propose a hashing model using two separated modules. A 3DCNN is proposed with a bidirectional encoder representations from transformers (BERT) layer. And a hashing neural network (...
2015-ICLR-Speeding-up convolutional neural networks using fine-tuned cp-decomposition 2015-ICML-Compressing neural networks with the hashing trick 2015-INTERSPEECH-A Diversity-Penalizing Ensemble Training Method for Deep Learning 2015-BMVC-Data-free parameter pruning for deep neural networks 2015-BMVC-Lear...
This technique gave rise to BERT [16], a breakthrough language model that was pre-trained using an enormous dataset, and that could be applied to a variety of different downstream tasks such as sentiment analysis. More recently, He et al. in [9] showed that this same concept can be ...
Multi-Kernel Diffusion CNNs for Graph-Based Learning on Point Clouds Lasse Hansen, Jasper Diesel, Mattias P. Heinrich ECCV 2018 Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network Feng Mao, Xiang Wu, Hui Xue, Rong Zhang ECCV 2018 Graph R-CNN for Scene Graph...
13315 In order to enhance the visual encoding mechanism for captioning purposes, GRU-EVE (Aafaq et al. 2019a) was the first to emphasize feature encoding for semantically robust descriptions using a 2D/3D CNN with short Fourier transform as a visual model and a two-layered GRU as a ...
CNN with minimal features was developed to address the vulnerabilities caused by network complexity and open broadcast characteristics of IoT networks. The performance of the CNN was verified using the NSL-KDD dataset11 which simulates intrusions in a multi-cloud IoT environment. Table 6 summarizes ...
Generating 3D Faces using Convolutional Mesh Autoencoders Anurag Ranjan, Timo Bolkart, Soubhik Sanyal, Michael J. Black ECCV 2018 Learning SO(3) Equivariant Representations with Spherical CNNs Carlos Esteves, Christine Allen-Blanchette, Ameesh Makadia, Kostas Daniilidis ECCV 2018 Neural Graph Match...
Multi-Kernel Diffusion CNNs for Graph-Based Learning on Point Clouds Lasse Hansen, Jasper Diesel, Mattias P. Heinrich ECCV 2018 Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network Feng Mao, Xiang Wu, Hui Xue, Rong Zhang ECCV 2018 Graph R-CNN for Scene Graph...
Multi-Kernel Diffusion CNNs for Graph-Based Learning on Point Clouds Lasse Hansen, Jasper Diesel, Mattias P. Heinrich ECCV 2018 Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network Feng Mao, Xiang Wu, Hui Xue, Rong Zhang ECCV 2018 Graph R-CNN for Scene Graph...
Multi-Kernel Diffusion CNNs for Graph-Based Learning on Point Clouds Lasse Hansen, Jasper Diesel, Mattias P. Heinrich ECCV 2018 Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network Feng Mao, Xiang Wu, Hui Xue, Rong Zhang ECCV 2018 Graph R-CNN for Scene Graph...