Ai alignment: A comprehensive survey
AI alignment aims to make AI systems behave in line with human intentions and values. As
AI systems grow more capable, the potential large-scale risks associated with misaligned AI …
AI systems grow more capable, the potential large-scale risks associated with misaligned AI …
Affordances from human videos as a versatile representation for robotics
Building a robot that can understand and learn to interact by watching humans has inspired
several vision problems. However, despite some successful results on static datasets, it …
several vision problems. However, despite some successful results on static datasets, it …
Foundation models for decision making: Problems, methods, and opportunities
Foundation models pretrained on diverse data at scale have demonstrated extraordinary
capabilities in a wide range of vision and language tasks. When such models are deployed …
capabilities in a wide range of vision and language tasks. When such models are deployed …
Mimicplay: Long-horizon imitation learning by watching human play
Imitation learning from human demonstrations is a promising paradigm for teaching robots
manipulation skills in the real world. However, learning complex long-horizon tasks often …
manipulation skills in the real world. However, learning complex long-horizon tasks often …
Structured world models from human videos
We tackle the problem of learning complex, general behaviors directly in the real world. We
propose an approach for robots to efficiently learn manipulation skills using only a handful of …
propose an approach for robots to efficiently learn manipulation skills using only a handful of …
Roboagent: Generalization and efficiency in robot manipulation via semantic augmentations and action chunking
The grand aim of having a single robot that can manipulate arbitrary objects in diverse
settings is at odds with the paucity of robotics datasets. Acquiring and growing such datasets …
settings is at odds with the paucity of robotics datasets. Acquiring and growing such datasets …
Diff-lfd: Contact-aware model-based learning from visual demonstration for robotic manipulation via differentiable physics-based simulation and rendering
Abstract Learning from Demonstration (LfD) is an efficient technique for robots to acquire
new skills through expert observation, significantly mitigating the need for laborious manual …
new skills through expert observation, significantly mitigating the need for laborious manual …
Towards a richer 2D understanding of hands at scale
As humans, we learn a lot about how to interact with the world by observing others
interacting with their hands. To help AI systems obtain a better understanding of hand …
interacting with their hands. To help AI systems obtain a better understanding of hand …
H-InDex: Visual reinforcement learning with hand-informed representations for dexterous manipulation
Human hands possess remarkable dexterity and have long served as a source of inspiration
for robotic manipulation. In this work, we propose a human $\textbf {H} $ and-$\textbf {In} …
for robotic manipulation. In this work, we propose a human $\textbf {H} $ and-$\textbf {In} …
An outlook into the future of egocentric vision
What will the future be? We wonder! In this survey, we explore the gap between current
research in egocentric vision and the ever-anticipated future, where wearable computing …
research in egocentric vision and the ever-anticipated future, where wearable computing …