Human Pose, Shape and Action
3D Pose from Images
2D Pose from Images
Beyond Motion Capture
Action and Behavior
Body Perception
Body Applications
Pose and Motion Priors
Clothing Models (2011-2015)
Reflectance Filtering
Learning on Manifolds
Markerless Animal Motion Capture
Multi-Camera Capture
2D Pose from Optical Flow
Body Perception
Neural Prosthetics and Decoding
Part-based Body Models
Intrinsic Depth
Lie Bodies
Layers, Time and Segmentation
Understanding Action Recognition (JHMDB)
Intrinsic Video
Intrinsic Images
Action Recognition with Tracking
Neural Control of Grasping
Flowing Puppets
Faces
Deformable Structures
Model-based Anthropometry
Modeling 3D Human Breathing
Optical flow in the LGN
FlowCap
Smooth Loops from Unconstrained Video
PCA Flow
Efficient and Scalable Inference
Motion Blur in Layers
Facade Segmentation
Smooth Metric Learning
Robust PCA
3D Recognition
Object Detection
Global Localization and Affordance Learning
Intelligent systems not only require the relative motion of objects around them [
][], but typically also a precise global location [] with respect to a map, i.e. for planning or navigation tasks. With LOST [], we have demonstrated that localization solely based on map information is feasible. For the creation of such maps, we have developed a method that correctly handles large-scale dynamic environments []
In [], we further showed that semantic and geometric information can significantly improve visual localization, allowing for localizing wrt. the opposite driving direction or in the presence of strong environmental changes.
Moreover, we have developed a novel model for sensori-motor control [] which learns driving affordances (such as the presence of obstacles or red lights, or the current speed limit) from video sequences using only very limited supervision. To foster new research on 3D scenes in motion, we have created a new dataset for 3D urban scene understanding, annotated at the object level [].
To provide an overview on the current problems, datasets and state-of-the-art, we have written a review paper on the topic [].
Project page "Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art"
Project page "Semantic Instance Annotation by 3D to 2D Label Transfer"
Video on "Conditional Affordance Learning for Driving in Urban Environments"
Project page "Robust Dense Mapping for Large-Scale Dynamic Environments"
Video on "Robust Dense Mapping for Large-Scale Dynamic Environments"
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