269 citations · 1k across the 33 of their papers we have counts for
5 papers · 1 filter
Grounded Video Description
Luowei Zhou, Yannis Kalantidis, Xinlei Chen +2
Video description is one of the most challenging problems in vision and language understanding due to the large variability both on the video and language side. Models, hence, typi…
Graph-Based Global Reasoning Networks
Yunpeng Chen, Marcus Rohrbach, Zhicheng Yan +3
Globally modeling and reasoning over relations between regions can be beneficial for many computer vision tasks on both images and videos. Convolutional Neural Networks (CNNs) exce…
-Nets: Double Attention Networks
Yunpeng Chen, Yannis Kalantidis, Jianshu Li +2
Learning to capture long-range relations is fundamental to image/video recognition. Existing CNN models generally rely on increasing depth to model such relations which is highly i…
Multi-Fiber Networks for Video Recognition
Yunpeng Chen, Yannis Kalantidis, Jianshu Li +2
In this paper, we aim to reduce the computational cost of spatio-temporal deep neural networks, making them run as fast as their 2D counterparts while preserving state-of-the-art a…
Large-Scale Visual Relationship Understanding
Ji Zhang, Yannis Kalantidis, Marcus Rohrbach +3
Large scale visual understanding is challenging, as it requires a model to handle the widely-spread and imbalanced distribution of <subject, relation, object> triples. In real-worl…