Objects are the core meaningful elements in our visual environment. Classic theories of
object vision focus upon object recognition and are elegant and simple. Some of their …

Nowadays, robots are dominating the manufacturing, entertainment, and healthcare
industries. Robot vision aims to equip robots with the capabilities to discover information …

Recent successes in image synthesis are powered by large-scale diffusion models.
However, most methods are currently limited to either text-or image-conditioned generation …

This paper presents ShapeLLM, the first 3D Multimodal Large Language Model (LLM)
designed for embodied interaction, exploring a universal 3D object understanding with 3D …

This review considers the evolution of economic thinking on the relationship between digital
technology and inequality across four decades, encompassing four related but intellectually …

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

We present a novel method for populating 3D indoor scenes with virtual humans that can
navigate in the environment and interact with objects in a realistic manner. Existing …

A long-standing goal in computer vision is to capture, model, and realistically synthesize
human behavior. Specifically, by learning from data, our goal is to enable virtual humans to …

We study the problem of inferring scene affordances by presenting a method for realistically
inserting people into scenes. Given a scene image with a marked region and an image of a …

To understand and analyze human behavior, we need to capture humans moving in, and
interacting with, the world. Most existing methods perform 3D human pose estimation …