There has been an emerging paradigm shift from the era of “internet AI” to “embodied AI,”
where AI algorithms and agents no longer learn from datasets of images, videos or text …

Despite significant advancements in text-to-motion synthesis generating language-guided
human motion within 3D environments poses substantial challenges. These challenges …

We introduce The House Of inteRactions (THOR), a framework for visual AI research,
available at http://ai2thor. allenai. org. AI2-THOR consists of near photo-realistic 3D indoor …

Realistic manipulation tasks require a robot to interact with an environment with a prolonged
sequence of motor actions. While deep reinforcement learning methods have recently …

One of the fundamental goals of visual perception is to allow agents to meaningfully interact
with their environment. In this paper, we take a step towards that long-term goal--we extract …

Visual affordance recognition is an important research topic in robotics, human-computer
interaction, and other computer vision tasks. In recent years, deep learning-based …

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 …

Existing 3D scene understanding methods are heavily focused on 3D semantic and instance
segmentation. However identifying objects and their parts only constitutes an intermediate …

Affordance grounding, a task to ground (ie, localize) action possibility region in objects,
which faces the challenge of establishing an explicit link with object parts due to the diversity …

Humans constantly contact objects to move and perform tasks. Thus, detecting human-
object contact is important for building human-centered artificial intelligence. However, there …