activity
20182020
most citedLearning Pairwise Relationship for Multi-object Detection in Crowded Scenes

9 citations · 21 across the 4 of their papers we have counts for

collaborators

9 papers

cs.CV20205 cited

Hyperspectral Classification Based on 3D Asymmetric Inception Network with Data Fusion Transfer Learning

Haokui Zhang, Yu Liu, Bei Fang +3

Hyperspectral image(HSI) classification has been improved with convolutional neural network(CNN) in very recent years. Being different from the RGB datasets, different HSI datasets…

cs.CV20194 cited

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…

cs.CV20193 cited

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…

cs.CV2019

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…

cs.CV2019

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…

cs.CV2019

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…