Search Results for author:
Found 7 papers, 2 papers with code
Gaussian Graph with Prototypical Contrastive Learning in E-Commerce Bundle Recommendation
In this paper, we propose a novel Gaussian Graph with Prototypical Contrastive Learning (GPCL) framework to overcome these challenges.
Dynamic Sampling Networks for Efficient Action Recognition in Videos
The existing action recognition methods are mainly based on clip-level classifiers such as two-stream CNNs or 3D CNNs, which are trained from the randomly selected clips and applied to densely sampled clips during testing.
Ranked #9 on
Action Recognition
on ActivityNet
Sequential Recommendation with Self-Attentive Multi-Adversarial Network
Recently, deep learning has made significant progress in the task of sequential recommendation.
TAM: Temporal Adaptive Module for Video Recognition
Video data is with complex temporal dynamics due to various factors such as camera motion, speed variation, and different activities.
TEINet: Towards an Efficient Architecture for Video Recognition
To relieve this problem, we propose an efficient temporal module, termed as Temporal Enhancement-and-Interaction (TEI Module), which could be plugged into the existing 2D CNNs (denoted by TEINet).
Cost-Effective Training of Deep CNNs with Active Model Adaptation
Deep convolutional neural networks have achieved great success in various applications.
IKM at SemEval-2017 Task 8: Convolutional Neural Networks for stance detection and rumor verification
This paper describes our approach for SemEval-2017 Task 8.
