495 citations · 2.9k across the 57 of their papers we have counts for
11 papers · 1 filter
Real-Time Semantic Segmentation via Multiply Spatial Fusion Network
Haiyang Si, Zhiqiang Zhang, Feifan Lv +2
Real-time semantic segmentation plays a significant role in industry applications, such as autonomous driving, robotics and so on. It is a challenging task as both efficiency and p…
SiamFC++: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelines
Yinda Xu, Zeyu Wang, Zuoxin Li +2
Visual tracking problem demands to efficiently perform robust classification and accurate target state estimation over a given target at the same time. Former methods have proposed…
Learnable Tree Filter for Structure-preserving Feature Transform
Lin Song, Yanwei Li, Zeming Li +4
Learning discriminative global features plays a vital role in semantic segmentation. And most of the existing methods adopt stacks of local convolutions or non-local blocks to capt…
Double Anchor R-CNN for Human Detection in a Crowd
Kevin Zhang, Feng Xiong, Peize Sun +3
Detecting human in a crowd is a challenging problem due to the uncertainties of occlusion patterns. In this paper, we propose to handle the crowd occlusion problem in human detecti…
Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection
Benjin Zhu, Zhengkai Jiang, Xiangxin Zhou +2
This report presents our method which wins the nuScenes3D Detection Challenge [17] held in Workshop on Autonomous Driving(WAD, CVPR 2019). Generally, we utilize sparse 3D convoluti…
Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network
Wenhai Wang, Enze Xie, Xiaoge Song +5
Scene text detection, an important step of scene text reading systems, has witnessed rapid development with convolutional neural networks. Nonetheless, two main challenges still ex…
TACNet: Transition-Aware Context Network for Spatio-Temporal Action Detection
Lin Song, Shiwei Zhang, Gang Yu +1
Current state-of-the-art approaches for spatio-temporal action detection have achieved impressive results but remain unsatisfactory for temporal extent detection. The main reason c…
An End-to-End Network for Panoptic Segmentation
Huanyu Liu, Chao Peng, Changqian Yu +4
Panoptic segmentation, which needs to assign a category label to each pixel and segment each object instance simultaneously, is a challenging topic. Traditionally, the existing app…
ThunderNet: Towards Real-time Generic Object Detection
Zheng Qin, Zeming Li, Zhaoning Zhang +4
Real-time generic object detection on mobile platforms is a crucial but challenging computer vision task. However, previous CNN-based detectors suffer from enormous computational c…
WIDER Face and Pedestrian Challenge 2018: Methods and Results
Chen Change Loy, Dahua Lin, Wanli Ouyang +49
This paper presents a review of the 2018 WIDER Challenge on Face and Pedestrian. The challenge focuses on the problem of precise localization of human faces and bodies, and accurat…
Rethinking on Multi-Stage Networks for Human Pose Estimation
Wenbo Li, Zhicheng Wang, Binyi Yin +7
Existing pose estimation approaches fall into two categories: single-stage and multi-stage methods. While multi-stage methods are seemingly more suited for the task, their performa…