Search Results for author:
Found 12 papers, 10 papers with code
Semi-Supervised Unconstrained Head Pose Estimation in the Wild
Existing head pose estimation datasets are either composed of numerous samples by non-realistic synthesis or lab collection, or limited images by labor-intensive annotating.
Boosting Semi-Supervised 2D Human Pose Estimation by Revisiting Data Augmentation and Consistency Training
The 2D human pose estimation (HPE) is a basic visual problem.
PBADet: A One-Stage Anchor-Free Approach for Part-Body Association
The detection of human parts (e. g., hands, face) and their correct association with individuals is an essential task, e. g., for ubiquitous human-machine interfaces and action recognition.
Contrast, Stylize and Adapt: Unsupervised Contrastive Learning Framework for Domain Adaptive Semantic Segmentation
To address this, we present CONtrastive FEaTure and pIxel alignment (CONFETI) for bridging the domain gap at both the pixel and feature levels using a unique contrastive formulation.
BPJDet: Extended Object Representation for Generic Body-Part Joint Detection
In this paper, we focus on the joint detection of human body and its parts.
DirectMHP: Direct 2D Multi-Person Head Pose Estimation with Full-range Angles
We present comprehensive comparisons with state-of-the-art single HPE methods on public benchmarks, as well as superior baseline results on our constructed MPHPE datasets.
Body-Part Joint Detection and Association via Extended Object Representation
This paper focuses on the problem of joint detection of human body and its corresponding parts.
An Intuitive and Unconstrained 2D Cube Representation for Simultaneous Head Detection and Pose Estimation
Most recent head pose estimation (HPE) methods are dominated by the Euler angle representation.
Ranked #8 on
Head Pose Estimation
on BIWI
(MAE (trained with BIWI data) metric)
StuArt: Individualized Classroom Observation of Students with Automatic Behavior Recognition and Tracking
In this paper, we present StuArt, a novel automatic system designed for the individualized classroom observation, which empowers instructors to concern the learning status of each student.
SSDA-YOLO: Semi-supervised Domain Adaptive YOLO for Cross-Domain Object Detection
Domain adaptive object detection (DAOD) aims to alleviate transfer performance degradation caused by the cross-domain discrepancy.
Joint Multi-Person Body Detection and Orientation Estimation via One Unified Embedding
In the paper, we propose a single-stage end-to-end trainable framework for tackling the HBOE problem with multi-persons.
Student Dangerous Behavior Detection in School
Video surveillance systems have been installed to ensure the student safety in schools.
