# Cloth Region Segmentation for Robust Grasp Selection

arXiv: https://arxiv.org/abs/2008.05626 · HTML: https://mlsanity.com/paper/2008.05626/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Aug 2020.

## Built on by (most cited first, 16 of 16)

- [Mesh-based Dynamics with Occlusion Reasoning for Cloth Manipulation](https://mlsanity.com/paper/2206.02881/) (2022)
- [Visuotactile Affordances for Cloth Manipulation with Local Control](https://mlsanity.com/paper/2212.05108/) (2022)
- [Learning Keypoints for Robotic Cloth Manipulation using Synthetic Data](https://mlsanity.com/paper/2401.01734/) (2024)
- [TraKDis: A Transformer-based Knowledge Distillation Approach for Visual Reinforcement Learning with Application to Cloth Manipulation](https://mlsanity.com/paper/2401.13362/) (2024)
- [InstructionBench: An Instructional Video Understanding Benchmark](https://mlsanity.com/paper/2504.05040/) (2025)
- [Enabling Visual Action Planning for Object Manipulation through Latent Space Roadmap](https://mlsanity.com/paper/2103.02554/) (2021)
- [Grasp-Oriented Fine-grained Cloth Segmentation without Real Supervision](https://mlsanity.com/paper/2110.02903/) (2021)
- [Smart Fashion: A Review of AI Applications in the Fashion & Apparel Industry](https://mlsanity.com/paper/2111.00905/) (2021)
- [Reactive In-Air Clothing Manipulation with Confidence-Aware Dense Correspondence and Visuotactile Affordance](https://mlsanity.com/paper/2509.03889/) (2025)
- [All You Need is LUV: Unsupervised Collection of Labeled Images using Invisible UV Fluorescent Indicators](https://mlsanity.com/paper/2203.04566/) (2022)
- [Center Direction Network for Grasping Point Localization on Cloths](https://mlsanity.com/paper/2408.14456/) (2024)
- [Clothes Grasping and Unfolding Based on RGB-D Semantic Segmentation](https://mlsanity.com/paper/2305.03259/) (2023)
- [RaggeDi: Diffusion-based State Estimation of Disordered Rags, Sheets, Towels and Blankets](https://mlsanity.com/paper/2409.11831/) (2024)
- [SKT: Integrating State-Aware Keypoint Trajectories with Vision-Language Models for Robotic Garment Manipulation](https://mlsanity.com/paper/2409.18082/) (2024)
- [The dGLI Cloth Coordinates: A Topological Representation for Semantic Classification of Cloth States](https://mlsanity.com/paper/2209.09191/) (2022)
- [Autonomous Quilt Spreading for Caregiving Robots](https://mlsanity.com/paper/2405.15373/) (2024)

## Abstract (arXiv)

Cloth detection and manipulation is a common task in domestic and industrial settings, yet such tasks remain a challenge for robots due to cloth deformability. Furthermore, in many cloth-related tasks like laundry folding and bed making, it is crucial to manipulate specific regions like edges and corners, as opposed to folds. In this work, we focus on the problem of segmenting and grasping these key regions. Our approach trains a network to segment the edges and corners of a cloth from a depth image, distinguishing such regions from wrinkles or folds. We also provide a novel algorithm for estimating the grasp location, direction, and directional uncertainty from the segmentation. We demonstrate our method on a real robot system and show that it outperforms baseline methods on grasping success. Video and other supplementary materials are available at: https://sites.google.com/view/cloth-segmentation.