794 citations · 4.3k across the 55 of their papers we have counts for
7 papers · 1 filter
Weakly Supervised Dense Event Captioning in Videos
Xuguang Duan, Wenbing Huang, Chuang Gan +3
Dense event captioning aims to detect and describe all events of interest contained in a video. Despite the advanced development in this area, existing methods tackle this task by…
Accelerating Deep Neural Networks with Spatial Bottleneck Modules
Junran Peng, Lingxi Xie, Zhaoxiang Zhang +2
This paper presents an efficient module named spatial bottleneck for accelerating the convolutional layers in deep neural networks. The core idea is to decompose convolution into t…
OCNet: Object Context Network for Scene Parsing
Yuhui Yuan, Lang Huang, Jianyuan Guo +3
In this paper, we address the semantic segmentation task with a new context aggregation scheme named \emph{object context}, which focuses on enhancing the role of object informatio…
IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks
Ke Sun, Mingjie Li, Dong Liu +1
In this paper, we are interested in building lightweight and efficient convolutional neural networks. Inspired by the success of two design patterns, composition of structured spar…
Part-Aligned Bilinear Representations for Person Re-identification
Yumin Suh, Jingdong Wang, Siyu Tang +2
We propose a novel network that learns a part-aligned representation for person re-identification. It handles the body part misalignment problem, that is, body parts are misaligned…
IGCV: Interleaved Structured Sparse Convolutional Neural Networks
Guotian Xie, Jingdong Wang, Ting Zhang +3
In this paper, we study the problem of designing efficient convolutional neural network architectures with the interest in eliminating the redundancy in convolution kernels. In add…
Object Detection in Videos by High Quality Object Linking
Peng Tang, Chunyu Wang, Xinggang Wang +3
Compared with object detection in static images, object detection in videos is more challenging due to degraded image qualities. An effective way to address this problem is to expl…