Search Results for author:
Found 7 papers, 2 papers with code
Transformer-Based Learned Optimization
We propose a new approach to learned optimization where we represent the computation of an optimizer's update step using a neural network.
Differentiable Dynamics for Articulated 3d Human Motion Reconstruction
We introduce DiffPhy, a differentiable physics-based model for articulated 3d human motion reconstruction from video.
Ranked #46 on
3D Human Pose Estimation
on Human3.6M
Trajectory Optimization for Physics-Based Reconstruction of 3d Human Pose from Monocular Video
We focus on the task of estimating a physically plausible articulated human motion from monocular video.
Ranked #296 on
3D Human Pose Estimation
on Human3.6M
Embodied Learning for Lifelong Visual Perception
As we study this task in a lifelong learning context, the agents should use knowledge gained in earlier visited environments in order to guide their exploration and active learning strategy in successively visited buildings.
Embodied Visual Active Learning for Semantic Segmentation
We study the task of embodied visual active learning, where an agent is set to explore a 3d environment with the goal to acquire visual scene understanding by actively selecting views for which to request annotation.
Deep Reinforcement Learning for Active Human Pose Estimation
Most 3d human pose estimation methods assume that input -- be it images of a scene collected from one or several viewpoints, or from a video -- is given.
Domes to Drones: Self-Supervised Active Triangulation for 3D Human Pose Reconstruction
In order to address the view selection problem in a principled way, we here introduce ACTOR, an active triangulation agent for 3d human pose reconstruction.
