1 citations · 1 across the 3 of their papers we have counts for
7 papers
SMooDi: Stylized Motion Diffusion Model
Lei Zhong, Yiming Xie, Varun Jampani +2
We introduce a novel Stylized Motion Diffusion model, dubbed SMooDi, to generate stylized motion driven by content texts and style motion sequences. Unlike existing methods that ei…
Probing the 3D Awareness of Visual Foundation Models
Mohamed El Banani, Amit Raj, Kevis-Kokitsi Maninis +7
Recent advances in large-scale pretraining have yielded visual foundation models with strong capabilities. Not only can recent models generalize to arbitrary images for their train…
SHINOBI: Shape and Illumination using Neural Object Decomposition via BRDF Optimization In-the-wild
Andreas Engelhardt, Amit Raj, Mark Boss +8
We present SHINOBI, an end-to-end framework for the reconstruction of shape, material, and illumination from object images captured with varying lighting, pose, and background. Inv…
HOI-Diff: Text-Driven Synthesis of 3D Human-Object Interactions using Diffusion Models
Xiaogang Peng, Yiming Xie, Zizhao Wu +3
We address the problem of generating realistic 3D human-object interactions (HOIs) driven by textual prompts. To this end, we take a modular design and decompose the complex task i…
One-Shot Open Affordance Learning with Foundation Models
Gen Li, Deqing Sun, Laura Sevilla-Lara +1
We introduce One-shot Open Affordance Learning (OOAL), where a model is trained with just one example per base object category, but is expected to identify novel objects and afford…
Telling Left from Right: Identifying Geometry-Aware Semantic Correspondence
Junyi Zhang, Charles Herrmann, Junhwa Hur +4
While pre-trained large-scale vision models have shown significant promise for semantic correspondence, their features often struggle to grasp the geometry and orientation of insta…