22 citations · 64 across the 9 of their papers we have counts for
6 papers · 1 filter
Gradient Information Guided Deraining with A Novel Network and Adversarial Training
Yinglong Wang, Haokui Zhang, Yu Liu +2
In recent years, deep learning based methods have made significant progress in rain-removing. However, the existing methods usually do not have good generalization ability, which l…
Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation
Yu Liu, Lingqiao Liu, Haokui Zhang +2
This paper tackles the problem of video object segmentation. We are specifically concerned with the task of segmenting all pixels of a target object in all frames, given the annota…
In defense of OSVOS
Yu Liu, Yutong Dai, Anh-Dzung Doan +2
As a milestone for video object segmentation, one-shot video object segmentation (OSVOS) has achieved a large margin compared to the conventional optical-flow based methods regardi…
Exploiting temporal consistency for real-time video depth estimation
Haokui Zhang, Chunhua Shen, Ying Li +3
Accuracy of depth estimation from static images has been significantly improved recently, by exploiting hierarchical features from deep convolutional neural networks (CNNs). Compar…
Scalable Place Recognition Under Appearance Change for Autonomous Driving
Anh-Dzung Doan, Yasir Latif, Tat-Jun Chin +3
A major challenge in place recognition for autonomous driving is to be robust against appearance changes due to short-term (e.g., weather, lighting) and long-term (seasons, vegetat…
Learning Pairwise Relationship for Multi-object Detection in Crowded Scenes
Yu Liu, Lingqiao Liu, Hamid Rezatofighi +3
As the post-processing step for object detection, non-maximum suppression (GreedyNMS) is widely used in most of the detectors for many years. It is efficient and accurate for spars…