activity
20242026
most citedHUMOS: Human Motion Model Conditioned on Body Shape

1 citations · 2 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2026

IMAGIN-4D: Image-Guided Controllable Interaction Generation

Sai Kumar Dwivedi, Federica Bogo, Buğra Tekin +6

Generating human-object interactions (HOI) is central to character animation, robotics, AR/VR, and embodied AI. Recent HOI generation methods synthesize motion from text, object ge…

cs.CV2026

UMO: Unified In-Context Learning Unlocks Motion Foundation Model Priors

Xiaoyan Cong, Zekun Li, Zhiyang Dou +9

Large-scale foundation models (LFMs) have recently made impressive progress in text-to-motion generation by learning strong generative priors from massive 3D human motion datasets…

cs.CV2026

NGL: Natural Garment Language for Training-Free Sewing Pattern Estimation

Anna Badalyan, Pratheba Selvaraju, Giorgio Becherini +3

Estimating sewing patterns from images is a practical approach for creating high-quality 3D garments, but it remains challenging due to the scarcity of paired real-world image and…

cs.CV2025

Moving by Looking: Towards Vision-Driven Avatar Motion Generation

Markos Diomataris, Berat Mert Albaba, Giorgio Becherini +3

The way we perceive the world fundamentally shapes how we move, whether it is how we navigate in a room or how we interact with other humans. Current human motion generation method…

cs.CV2025

PICO: Reconstructing 3D People In Contact with Objects

Alpár Cseke, Shashank Tripathi, Sai Kumar Dwivedi +4

Recovering 3D Human-Object Interaction (HOI) from single color images is challenging due to depth ambiguities, occlusions, and the huge variation in object shape and appearance. Th…

cs.CV2025

InteractVLM: 3D Interaction Reasoning from 2D Foundational Models

Sai Kumar Dwivedi, Dimitrije Antić, Shashank Tripathi +4

We introduce InteractVLM, a novel method to estimate 3D contact points on human bodies and objects from single in-the-wild images, enabling accurate human-object joint reconstructi…

cs.CV2025

NIL: No-data Imitation Learning by Leveraging Pre-trained Video Diffusion Models

Mert Albaba, Chenhao Li, Markos Diomataris +3

Acquiring physically plausible motor skills across diverse and unconventional morphologies-including humanoid robots, quadrupeds, and animals-is essential for advancing character s…

cs.CV2024★ 1 cited

HUMOS: Human Motion Model Conditioned on Body Shape

Shashank Tripathi, Omid Taheri, Christoph Lassner +3

Generating realistic human motion is essential for many computer vision and graphics applications. The wide variety of human body shapes and sizes greatly impacts how people move.…

cs.CV2024★ 1 cited

WANDR: Intention-guided Human Motion Generation

Markos Diomataris, Nikos Athanasiou, Omid Taheri +3

Synthesizing natural human motions that enable a 3D human avatar to walk and reach for arbitrary goals in 3D space remains an unsolved problem with many applications. Existing meth…