Search Results for author: Xiaolong Liu

Found 12 papers, 6 papers with code

DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation

1 code implementation18 Nov 2022 Liangwei Yang, Shengjie Wang, Yunzhe Tao, Jiankai Sun, Xiaolong Liu, Philip S. Yu, Taiqing Wang

Graph Neural Network (GNN) based recommender systems have been attracting more and more attention in recent years due to their excellent performance in accuracy.

Recommendation Systems

Ranking-based Group Identification via Factorized Attention on Social Tripartite Graph

1 code implementation2 Nov 2022 Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

PA layers efficiently learn the relatedness of non-neighbor nodes to improve the information propagation to users.

Multi-Task Learning Framework for Emotion Recognition in-the-wild

1 code implementation19 Jul 2022 Tenggan Zhang, Chuanhe Liu, Xiaolong Liu, Yuchen Liu, Liyu Meng, Lei Sun, Wenqiang Jiang, Fengyuan Zhang, Jinming Zhao, Qin Jin

This paper presents our system for the Multi-Task Learning (MTL) Challenge in the 4th Affective Behavior Analysis in-the-wild (ABAW) competition.

Emotion Recognition Multi-Task Learning +1

An Empirical Study of End-to-End Temporal Action Detection

1 code implementation CVPR 2022 Xiaolong Liu, Song Bai, Xiang Bai

Rather than end-to-end learning, most existing methods adopt a head-only learning paradigm, where the video encoder is pre-trained for action classification, and only the detection head upon the encoder is optimized for TAD.

Action Classification Action Detection +2

Multi-modal Emotion Estimation for in-the-wild Videos

no code implementations24 Mar 2022 Liyu Meng, Yuchen Liu, Xiaolong Liu, Zhaopei Huang, Yuan Cheng, Meng Wang, Chuanhe Liu, Qin Jin

In this paper, we briefly introduce our submission to the Valence-Arousal Estimation Challenge of the 3rd Affective Behavior Analysis in-the-wild (ABAW) competition.

Arousal Estimation

End-to-end Temporal Action Detection with Transformer

1 code implementation18 Jun 2021 Xiaolong Liu, Qimeng Wang, Yao Hu, Xu Tang, Shiwei Zhang, Song Bai, Xiang Bai

Temporal action detection (TAD) aims to determine the semantic label and the temporal interval of every action instance in an untrimmed video.

Action Detection Temporal Action Localization +1

Localization and Control of Magnetic Suture Needles in Cluttered Surgical Site with Blood and Tissue

no code implementations20 May 2021 Will Pryor, Yotam Barnoy, Suraj Raval, Xiaolong Liu, Lamar Mair, Daniel Lerner, Onder Erin, Gregory D. Hager, Yancy Diaz-Mercado, Axel Krieger

Our localization method combines neural network-based segmentation and classical techniques, and we are able to consistently locate our needle with 0. 73 mm RMS error in clean environments and 2. 72 mm RMS error in challenging environments with blood and occlusion.

Visual Localization

CASNet: Common Attribute Support Network for image instance and panoptic segmentation

no code implementations17 Jul 2020 Xiaolong Liu, Yuqing Hou, Anbang Yao, Yurong Chen, Keqiang Li

Given the insight that pixels belonging to one instance have one or more common attributes of current instance, we bring up an one-stage instance segmentation network named Common Attribute Support Network (CASNet), which realizes instance segmentation by predicting and clustering common attributes.

Instance Segmentation object-detection +2

Recent progress in semantic image segmentation

no code implementations20 Sep 2018 Xiaolong Liu, Zhidong Deng, Yuhan Yang

In this paper, we divide semantic image segmentation methods into two categories: traditional and recent DNN method.

Image Segmentation Semantic Segmentation

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