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Ruining Li

University of Oxford, Visual Geometry Group

12 papers hereh-index 8354 citations13 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author6
  • middle author6

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CV11
  • cs.LG1
affiliations
  • University of Oxford, Visual Geometry Group
Homepage
same name
  • Ruining Li — 1 paper
  • Ruining Li — 1 paper, h 0

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212026
most citedDragAPart: Learning a Part-Level Motion Prior for Articulated Objects

1 citations · 2 across the 11 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.CV2024

DreamHOI: Subject-Driven Generation of 3D Human-Object Interactions with Diffusion Priors

Thomas Hanwen Zhu, Ruining Li, Tomas Jakab

We present DreamHOI, a novel method for zero-shot synthesis of human-object interactions (HOIs), enabling a 3D human model to realistically interact with any given object based on…

cs.CV2024

Puppet-Master: Scaling Interactive Video Generation as a Motion Prior for Part-Level Dynamics

Ruining Li, Chuanxia Zheng, Christian Rupprecht +1

We introduce Puppet-Master, an interactive video generator that captures the internal, part-level motion of objects, serving as a proxy for modeling object dynamics universally. Gi…

cs.CV2024★ 1 cited

DragAPart: Learning a Part-Level Motion Prior for Articulated Objects

Ruining Li, Chuanxia Zheng, Christian Rupprecht +1

We introduce DragAPart, a method that, given an image and a set of drags as input, generates a new image of the same object that responds to the action of the drags. Differently fr…

cs.CV2024

Learning the 3D Fauna of the Web

Zizhang Li, Dor Litvak, Ruining Li +6

Learning 3D models of all animals on the Earth requires massively scaling up existing solutions. With this ultimate goal in mind, we develop 3D-Fauna, an approach that learns a pan…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.