We propose a simulation environment, VT-Sim, which supports generating hand-object interaction for both rigid and deformable objects.
In this work, we explore the freestyle capability of the model, i. e., how far can it generate unseen semantics (e. g., classes, attributes, and styles) onto a given layout, and call the task Freestyle LIS (FLIS).
In this work, we present a complete package to address the category-level garment pose tracking task: (1) A recording system VR-Garment, with which users can manipulate virtual garment models in simulation through a VR interface.
With the full representation of the object shape and joint states, we can address several tasks including category-level object pose estimation and the articulated object retrieval.
To ensure the visual style consistency between the foreground and the background, in this paper, we treat image harmonization as a style transfer problem.
Ranked #3 on Image Harmonization on HAdobe5k(1024$\times$1024)
This setting allows varied kinematic structures within a semantic category, and multiple instances to co-exist in an observation of real world.
Previous methods edit an input image under the guidance of a discrete emotion label or absolute condition (e. g., facial action units) to possess the desired expression.
We present a new object representation, called Dense RepPoints, that utilizes a large set of points to describe an object at multiple levels, including both box level and pixel level.
Learning autonomous-driving policies is one of the most challenging but promising tasks for computer vision.