Search Results for author:
Found 7 papers, 2 papers with code
OriNet: A Fully Convolutional Network for 3D Human Pose Estimation
We use limb orientations as a new way to represent 3D poses and bind the orientation together with the bounding box of each limb region to better associate images and predictions.
Ranked #76 on
3D Human Pose Estimation
on MPI-INF-3DHP
(AUC metric)
Visual Question Generation as Dual Task of Visual Question Answering
Recently visual question answering (VQA) and visual question generation (VQG) are two trending topics in the computer vision, which have been explored separately.
Multi-Context Attention for Human Pose Estimation
We further combine the holistic attention model, which focuses on the global consistency of the full human body, and the body part attention model, which focuses on the detailed description for different body parts.
Ranked #8 on
Pose Estimation
on Leeds Sports Poses
CRF-CNN: Modeling Structured Information in Human Pose Estimation
In a classical neural network, there is no message passing between neurons in the same layer.
Structured Feature Learning for Pose Estimation
In this paper, we propose a structured feature learning framework to reason the correlations among body joints at the feature level in human pose estimation.
Multi-Task Recurrent Neural Network for Immediacy Prediction
In this paper, we propose to predict immediacy for interacting persons from still images.
Multi-source Deep Learning for Human Pose Estimation
Visual appearance score, appearance mixture type and deformation are three important information sources for human pose estimation.
