activity
20162021
most citedEdge Preserving and Multi-Scale Contextual Neural Network for Salient Object Detection

127 citations · 409 across the 15 of their papers we have counts for

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12 papers · 1 filter

cs.CV2021★ 1 cited

Video Frame Interpolation via Structure-Motion based Iterative Fusion

Xi Li, Meng Cao, Yingying Tang +4

Video Frame Interpolation synthesizes non-existent images between adjacent frames, with the aim of providing a smooth and consistent visual experience. Two approaches for solving t…

cs.CV2020

Unsupervised segmentation via semantic-apparent feature fusion

Xi Li, Huimin Ma, Hongbing Ma +1

Foreground segmentation is an essential task in the field of image understanding. Under unsupervised conditions, different images and instances always have variable expressions, wh…

cs.CV2020

Realizing Pixel-Level Semantic Learning in Complex Driving Scenes based on Only One Annotated Pixel per Class

Xi Li, Huimin Ma, Sheng Yi +1

Semantic segmentation tasks based on weakly supervised condition have been put forward to achieve a lightweight labeling process. For simple images that only include a few categori…

cs.CV2020★ 89 cited

Weakly-Supervised Semantic Segmentation by Iterative Affinity Learning

Xiang Wang, Sifei Liu, Huimin Ma +1

Weakly-supervised semantic segmentation is a challenging task as no pixel-wise label information is provided for training. Recent methods have exploited classification networks to…

cs.CV2019★ 5 cited

Semantic Head Enhanced Pedestrian Detection in a Crowd

Ruiqi Lu, Huimin Ma

Pedestrian detection in the crowd is a challenging task because of intra-class occlusion. More prior information is needed for the detector to be robust against it. Human head area…

cs.CV2019★ 2 cited

WSOD with PSNet and Box Regression

Sheng Yi, Xi Li, Huimin Ma

Weakly supervised object detection(WSOD) task uses only image-level annotations to train object detection task. WSOD does not require time-consuming instance-level annotations, so…

cs.CV2019

Occluded Pedestrian Detection with Visible IoU and Box Sign Predictor

Ruiqi Lu, Huimin Ma

Training a robust classifier and an accurate box regressor are difficult for occluded pedestrian detection. Traditionally adopted Intersection over Union (IoU) measurement does not…

cs.CV2018★ 35 cited

Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features

Xiang Wang, Shaodi You, Xi Li +1

Weakly-supervised semantic segmentation under image tags supervision is a challenging task as it directly associates high-level semantic to low-level appearance. To bridge this gap…

cs.CV2016

Single Image Action Recognition using Semantic Body Part Actions

Zhichen Zhao, Huimin Ma, Shaodi You

In this paper, we propose a novel single image action recognition algorithm which is based on the idea of semantic body part actions. Unlike existing bottom up methods, we argue th…

cs.CV2016★ 65 cited

Multi-View 3D Object Detection Network for Autonomous Driving

Xiaozhi Chen, Huimin Ma, Ji Wan +2

This paper aims at high-accuracy 3D object detection in autonomous driving scenario. We propose Multi-View 3D networks (MV3D), a sensory-fusion framework that takes both LIDAR poin…

cs.CV2016★ 127 cited

Edge Preserving and Multi-Scale Contextual Neural Network for Salient Object Detection

Xiang Wang, Huimin Ma, Xiaozhi Chen +1

In this paper, we propose a novel edge preserving and multi-scale contextual neural network for salient object detection. The proposed framework is aiming to address two limits of…

cs.CV2016★ 49 cited

3D Object Proposals using Stereo Imagery for Accurate Object Class Detection

Xiaozhi Chen, Kaustav Kundu, Yukun Zhu +3

The goal of this paper is to perform 3D object detection in the context of autonomous driving. Our method first aims at generating a set of high-quality 3D object proposals by expl…