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Found 9 papers, 5 papers with code
Prototype Learning for Micro-gesture Classification
In this paper, we briefly introduce the solution developed by our team, HFUT-VUT, for the track of Micro-gesture Classification in the MiGA challenge at IJCAI 2024.
MMAD: Multi-label Micro-Action Detection in Videos
To support the MMAD task, we introduce a new dataset named Multi-label Micro-Action-52 (MMA-52), specifically designed to facilitate the detailed analysis and exploration of complex human micro-actions.
Micro-gesture Online Recognition using Learnable Query Points
The Micro-gesture Online Recognition task involves identifying the category and locating the start and end times of micro-gestures in video clips.
SimPB: A Single Model for 2D and 3D Object Detection from Multiple Cameras
The field of autonomous driving has attracted considerable interest in approaches that directly infer 3D objects in the Bird's Eye View (BEV) from multiple cameras.
Dual-Path Temporal Map Optimization for Make-up Temporal Video Grounding
Compared with the general video grounding task, MTVG focuses on meticulous actions and changes on the face.
Data Augmentation for Human Behavior Analysis in Multi-Person Conversations
In this paper, we present the solution of our team HFUT-VUT for the MultiMediate Grand Challenge 2023 at ACM Multimedia 2023.
Joint Skeletal and Semantic Embedding Loss for Micro-gesture Classification
In this paper, we briefly introduce the solution of our team HFUT-VUT for the Micros-gesture Classification in the MiGA challenge at IJCAI 2023.
Ranked #1 on
Micro-gesture Recognition
on iMiGUE
A comparison study: the impact of age and gender distribution on age estimation
In this work, we analyze the age and gender distribution of previous datasets and publish an Uniform Age and Gender Dataset (UAGD) which has almost equal number of female and male images in each age.
Combinatorial Multi-Armed Bandit Based Unknown Worker Recruitment in Heterogeneous Crowdsensing
In each round, every task may be covered by more than one recruited workers, but its completion quality only depends on these workers' maximum sensing quality.
