Search Results for author:
Found 7 papers, 4 papers with code
Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design
Specifically, we learn a conditional policy that, in an episode, first applies a sequence of transform actions to modify an agent's skeletal structure and joint attributes, and then applies control actions under the new design.
Dynamics-Regulated Kinematic Policy for Egocentric Pose Estimation
By comparing the pose instructed by the kinematic model against the pose generated by the dynamics model, we can use their misalignment to further improve the kinematic model.
Egocentric Pose Estimation
Human-Object Interaction Detection
+1
Kinematics-Guided Reinforcement Learning for Object-Aware 3D Ego-Pose Estimation
We propose a method for incorporating object interaction and human body dynamics into the task of 3D ego-pose estimation using a head-mounted camera.
3D Human Motion Estimation via Motion Compression and Refinement
Experiments show that our method produces both smooth and accurate 3D human pose and motion estimates.
Ranked #1 on
3D Human Pose Estimation
on MPI-INF-3DHP
(MJPE metric, using extra
training data)
Learning Shape Representations for Clothing Variations in Person Re-Identification
To tackle the re-ID problem in the context of clothing changes, we propose a novel representation learning model which is able to generate a body shape feature representation without being affected by clothing color or patterns.
Cross-Domain 3D Equivariant Image Embeddings
This embedding encodes images with 3D shape properties and is equivariant to 3D rotations of the observed object.
Cloud Chaser: Real Time Deep Learning Computer Vision on Low Computing Power Devices
Internet of Things(IoT) devices, mobile phones, and robotic systems are often denied the power of deep learning algorithms due to their limited computing power.
