11 citations · 28 across the 10 of their papers we have counts for
10 papers
DeformMaster: An Interactive Physics-Neural World Model for Deformable Objects from Videos
Can Li, Zhoujian Li, Ren Li +4
World models for deformable objects should recover not only geometry and appearance, but also underlying physical dynamics, interaction grounding, and material behavior. Learning s…
ISP: Multi-Layered Garment Draping with Implicit Sewing Patterns
Ren Li, Benoît Guillard, Pascal Fua
Many approaches to draping individual garments on human body models are realistic, fast, and yield outputs that are differentiable with respect to the body shape on which they are…
DrapeNet: Garment Generation and Self-Supervised Draping
Luca De Luigi, Ren Li, Benoît Guillard +2
Recent approaches to drape garments quickly over arbitrary human bodies leverage self-supervision to eliminate the need for large training sets. However, they are designed to train…
DIG: Draping Implicit Garment over the Human Body
Ren Li, Benoît Guillard, Edoardo Remelli +1
Existing data-driven methods for draping garments over human bodies, despite being effective, cannot handle garments of arbitrary topology and are typically not end-to-end differen…
High-Fidelity Point Cloud Completion with Low-Resolution Recovery and Noise-Aware Upsampling
Ren-Wu Li, Bo Wang, Chun-Peng Li +2
Completing an unordered partial point cloud is a challenging task. Existing approaches that rely on decoding a latent feature to recover the complete shape, often lead to the compl…
Learning Local Recurrent Models for Human Mesh Recovery
Runze Li, Srikrishna Karanam, Ren Li +3
We consider the problem of estimating frame-level full human body meshes given a video of a person with natural motion dynamics. While much progress in this field has been in singl…
Everybody Is Unique: Towards Unbiased Human Mesh Recovery
Ren Li, Meng Zheng, Srikrishna Karanam +2
We consider the problem of obese human mesh recovery, i.e., fitting a parametric human mesh to images of obese people. Despite obese person mesh fitting being an important problem…
An Iteratively Optimized Patch Label Inference Network for Automatic Pavement Distress Detection
Wenhao Tang, Sheng Huang, Qiming Zhao +2
We present a novel deep learning framework named the Iteratively Optimized Patch Label Inference Network (IOPLIN) for automatically detecting various pavement distresses that are n…
Hierarchical Kinematic Human Mesh Recovery
Georgios Georgakis, Ren Li, Srikrishna Karanam +3
We consider the problem of estimating a parametric model of 3D human mesh from a single image. While there has been substantial recent progress in this area with direct regression…
Towards Robust RGB-D Human Mesh Recovery
Ren Li, Changjiang Cai, Georgios Georgakis +3
We consider the problem of human pose estimation. While much recent work has focused on the RGB domain, these techniques are inherently under-constrained since there can be many 3D…