Search Results for author: Jialin Gao

Found 8 papers, 3 papers with code

From 2D to 3D: AISG-SLA Visual Localization Challenge

no code implementations26 Jul 2024 Jialin Gao, Bill Ong, Darld Lwi, Zhen Hao Ng, Xun Wei Yee, Mun-Thye Mak, Wee Siong Ng, See-Kiong Ng, Hui Ying Teo, Victor Khoo, Georg Bökman, Johan Edstedt, Kirill Brodt, Clémentin Boittiaux, Maxime Ferrera, Stepan Konev

To tackle these challenges, we organized the AISG-SLA Visual Localization Challenge (VLC) at IJCAI 2023 to explore how AI can accurately extract camera pose data from 2D images in 3D space.

Pose Estimation Position +1

Boundary-Denoising for Video Activity Localization

1 code implementation6 Apr 2023 Mengmeng Xu, Mattia Soldan, Jialin Gao, Shuming Liu, Juan-Manuel Pérez-Rúa, Bernard Ghanem

To alleviate the boundary ambiguity, we propose to study the video activity localization problem from a denoising perspective.

Action Detection Decoder +3

You Need to Read Again: Multi-granularity Perception Network for Moment Retrieval in Videos

1 code implementation25 May 2022 Xin Sun, Xuan Wang, Jialin Gao, Qiong Liu, Xi Zhou

Moment retrieval in videos is a challenging task that aims to retrieve the most relevant video moment in an untrimmed video given a sentence description.

Moment Retrieval Reading Comprehension +2

Focusing and Diffusion: Bidirectional Attentive Graph Convolutional Networks for Skeleton-based Action Recognition

no code implementations24 Dec 2019 Jialin Gao, Tong He, Xi Zhou, Shiming Ge

A collection of approaches based on graph convolutional networks have proven success in skeleton-based action recognition by exploring neighborhood information and dense dependencies between intra-frame joints.

Action Recognition Skeleton Based Action Recognition

Relation-Aware Pyramid Network (RapNet) for temporal action proposal

no code implementations9 Aug 2019 Jialin Gao, Zhixiang Shi, Jiani Li, Yufeng Yuan, Jiwei Li, Xi Zhou

In this technical report, we describe our solution to temporal action proposal (task 1) in ActivityNet Challenge 2019.

Relation

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