71 citations · 130 across the 13 of their papers we have counts for
13 papers
Weakly Supervised Video Representation Learning with Unaligned Text for Sequential Videos
Sixun Dong, Huazhang Hu, Dongze Lian +3
Sequential video understanding, as an emerging video understanding task, has driven lots of researchers' attention because of its goal-oriented nature. This paper studies weakly su…
SVIP: Sequence VerIfication for Procedures in Videos
Yicheng Qian, Weixin Luo, Dongze Lian +3
In this paper, we propose a novel sequence verification task that aims to distinguish positive video pairs performing the same action sequence from negative ones with step-level tr…
Two-stage Visual Cues Enhancement Network for Referring Image Segmentation
Yang Jiao, Zequn Jie, Weixin Luo +4
Referring Image Segmentation (RIS) aims at segmenting the target object from an image referred by one given natural language expression. The diverse and flexible expressions as wel…
Proxy-bridged Image Reconstruction Network for Anomaly Detection in Medical Images
Kang Zhou, Jing Li, Weixin Luo +6
Anomaly detection in medical images refers to the identification of abnormal images with only normal images in the training set. Most existing methods solve this problem with a sel…
Look Before You Leap: Learning Landmark Features for One-Stage Visual Grounding
Binbin Huang, Dongze Lian, Weixin Luo +1
An LBYL (`Look Before You Leap') Network is proposed for end-to-end trainable one-stage visual grounding. The idea behind LBYL-Net is intuitive and straightforward: we follow a lan…
Learning to Recommend Frame for Interactive Video Object Segmentation in the Wild
Zhaoyuan Yin, Jia Zheng, Weixin Luo +3
This paper proposes a framework for the interactive video object segmentation (VOS) in the wild where users can choose some frames for annotations iteratively. Then, based on the u…
Amodal Segmentation Based on Visible Region Segmentation and Shape Prior
Yuting Xiao, Yanyu Xu, Ziming Zhong +3
Almost all existing amodal segmentation methods make the inferences of occluded regions by using features corresponding to the whole image. This is against the human's amodal perce…
SIRI: Spatial Relation Induced Network For Spatial Description Resolution
Peiyao Wang, Weixin Luo, Yanyu Xu +4
Spatial Description Resolution, as a language-guided localization task, is proposed for target location in a panoramic street view, given corresponding language descriptions. Expli…
Encoding Structure-Texture Relation with P-Net for Anomaly Detection in Retinal Images
Kang Zhou, Yuting Xiao, Jianlong Yang +6
Anomaly detection in retinal image refers to the identification of abnormality caused by various retinal diseases/lesions, by only leveraging normal images in training phase. Norma…
Password-conditioned Anonymization and Deanonymization with Face Identity Transformers
Xiuye Gu, Weixin Luo, Michael S. Ryoo +1
Cameras are prevalent in our daily lives, and enable many useful systems built upon computer vision technologies such as smart cameras and home robots for service applications. How…
PPGNet: Learning Point-Pair Graph for Line Segment Detection
Ziheng Zhang, Zhengxin Li, Ning Bi +6
In this paper, we present a novel framework to detect line segments in man-made environments. Specifically, we propose to describe junctions, line segments and relationships betwee…
Multi-Cell Multi-Task Convolutional Neural Networks for Diabetic Retinopathy Grading
Kang Zhou, Zaiwang Gu, Wen Liu +4
Diabetic Retinopathy (DR) is a non-negligible eye disease among patients with Diabetes Mellitus, and automatic retinal image analysis algorithm for the DR screening is in high dema…
Future Frame Prediction for Anomaly Detection -- A New Baseline
Wen Liu, Weixin Luo, Dongze Lian +1
Anomaly detection in videos refers to the identification of events that do not conform to expected behavior. However, almost all existing methods tackle the problem by minimizing t…