From the 1 of 8 linked papers with an AI index.
8 papers
Learning-based Seam Correspondence Reconstruction in Sewing Patterns
Zhendong Wang, Jintong Wang, Chen Liu +3
Digital sewing patterns typically consist of disjoint 2D panels without explicit stitch annotations, making downstream 3D modeling reliant on labor-intensive expert specification.…
Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents
Guanxiong Chen, Qianjun Xia, Jiawei Peng +21
Real-to-sim conversion for robotic interaction with objects remains labor-intensive because it requires more than visual reconstruction: a streamlined real2sim process must recover…
TAMF-VTON: Texture-Aware Mask-Free Virtual Try-On via High-Fidelity Image Synthesis
Jie Wang, Qian He, Gaofeng He +2
The paper introduces TAMF-VTON, a diffusion-based virtual try‑on system that works without segmentation masks and can apply multiple garments while preserving fine texture details,…
SimWeaver: Zero-Shot RGB Sim-to-Real for Deformable Manipulation
Wenkang Hu, Haoran Wang, Yitong Li +10
RGB sim-to-real for deformable manipulation has remained largely unsolved without real-world fine-tuning. We present SimWeaver, which trains zero-shot RGB VLA policies on 200 simul…
Real Garment Benchmark (RGBench): A Comprehensive Benchmark for Robotic Garment Manipulation featuring a High-Fidelity Scalable Simulator
Wenkang Hu, Xincheng Tang, Yanzhi E +5
While there has been significant progress to use simulated data to learn robotic manipulation of rigid objects, applying its success to deformable objects has been hindered by the…
GarmageNet: A Multimodal Generative Framework for Sewing Pattern Design and Generic Garment Modeling
Siran Li, Ruiyang Liu, Chen Liu +5
Realistic digital garment modeling remains a labor-intensive task due to the intricate process of translating 2D sewing patterns into high-fidelity, simulation-ready 3D garments. W…