Adaafford: Learning to adapt manipulation affordance for 3d articulated objects via few-shot interactions
Perceiving and interacting with 3D articulated objects, such as cabinets, doors, and faucets,
pose particular challenges for future home-assistant robots performing daily tasks in human …
pose particular challenges for future home-assistant robots performing daily tasks in human …
Learning 3d dynamic scene representations for robot manipulation
3D scene representation for robot manipulation should capture three key object properties:
permanency--objects that become occluded over time continue to exist; amodal …
permanency--objects that become occluded over time continue to exist; amodal …
Alignnet: Unsupervised entity alignment
Recently developed deep learning models are able to learn to segment scenes into
component objects without supervision. This opens many new and exciting avenues of …
component objects without supervision. This opens many new and exciting avenues of …
Comprehensively Assessing the Landscape of Algorithmic Bias and Fairness Considerations in Modern AI Systems
M Jovanović - Eigenpub Review of Science and Technology, 2023 - studies.eigenpub.com
Algorithmic bias and fairness have become pressing concerns as artificial intelligence (AI)
systems are increasingly deployed in high-stakes domains like healthcare, criminal justice …
systems are increasingly deployed in high-stakes domains like healthcare, criminal justice …
AlignNet: Self-supervised Alignment Module
The natural world consists of objects that we perceive as persistent in space and time, even
though these objects appear, disappear and reappear in our field of view as we move. This …
though these objects appear, disappear and reappear in our field of view as we move. This …