Learning complex dexterous manipulation with deep reinforcement learning and demonstrations
Manipnet: neural manipulation synthesis with a hand-object spatial representation
Natural hand manipulations exhibit complex finger maneuvers adaptive to object shapes
and the tasks at hand. Learning dexterous manipulation from data in a brute force way …
and the tasks at hand. Learning dexterous manipulation from data in a brute force way …
Contactgen: Generative contact modeling for grasp generation
This paper presents a novel object-centric contact representation ContactGen for hand-
object interaction. The ContactGen comprises 3 components: a contact map indicates the …
object interaction. The ContactGen comprises 3 components: a contact map indicates the …
State of the art in hand and finger modeling and animation
The human hand is a complex biological system able to perform numerous tasks with
impressive accuracy and dexterity. Gestures furthermore play an important role in our daily …
impressive accuracy and dexterity. Gestures furthermore play an important role in our daily …
Cpf: Learning a contact potential field to model the hand-object interaction
Modeling the hand-object (HO) interaction not only requires estimation of the HO pose, but
also pays attention to the contact due to their interaction. Significant progress has been …
also pays attention to the contact due to their interaction. Significant progress has been …
Discovery of complex behaviors through contact-invariant optimization
We present a motion synthesis framework capable of producing a wide variety of important
human behaviors that have rarely been studied, including getting up from the ground …
human behaviors that have rarely been studied, including getting up from the ground …
Learning basketball dribbling skills using trajectory optimization and deep reinforcement learning
Basketball is one of the world's most popular sports because of the agility and speed
demonstrated by the players. This agility and speed makes designing controllers to realize …
demonstrated by the players. This agility and speed makes designing controllers to realize …
Toch: Spatio-temporal object-to-hand correspondence for motion refinement
We present TOCH, a method for refining incorrect 3D hand-object interaction sequences
using a correspondence based prior learnt directly from data. Existing hand trackers …
using a correspondence based prior learnt directly from data. Existing hand trackers …
Dynamics based 3D skeletal hand tracking
S Melax, L Keselman, S Orsten - … of the ACM SIGGRAPH Symposium on …, 2013 - dl.acm.org
Natural human computer interaction motivates hand tracking research, preferably without
requiring the user to wear special hardware or markers. Ideally, a hand tracking solution …
requiring the user to wear special hardware or markers. Ideally, a hand tracking solution …