Timezone: »
3D Garment modeling is a critical and challenging topic in the area of computer vision and graphics, with increasing attention focused on garment representation learning, garment reconstruction, and controllable garment manipulation, whereas existing methods were constrained to model garments under specific categories or with relatively simple topologies. In this paper, we propose a novel Neural Sewing Machine (NSM), a learning-based framework for structure-preserving 3D garment modeling, which is capable of learning representations for garments with diverse shapes and topologies and is successfully applied to 3D garment reconstruction and controllable manipulation. To model generic garments, we first obtain sewing pattern embedding via a unified sewing pattern encoding module, as the sewing pattern can accurately describe the intrinsic structure and the topology of the 3D garment. Then we use a 3D garment decoder to decode the sewing pattern embedding into a 3D garment using the UV-position maps with masks. To preserve the intrinsic structure of the predicted 3D garment, we introduce an inner-panel structure-preserving loss, an inter-panel structure-preserving loss, and a surface-normal loss in the learning process of our framework. We evaluate NSM on the public 3D garment dataset with sewing patterns with diverse garment shapes and categories. Extensive experiments demonstrate that the proposed NSM is capable of representing 3D garments under diverse garment shapes and topologies, realistically reconstructing 3D garments from 2D images with the preserved structure, and accurately manipulating the 3D garment categories, shapes, and topologies, outperforming the state-of-the-art methods by a clear margin.
Author Information
Xipeng Chen (SUN YAT-SEN UNIVERSITY)
Guangrun Wang (University of Oxford)
Dizhong Zhu (University of York)
Xiaodan Liang (Sun Yat-sen University)
Philip Torr (University of Oxford)
Liang Lin (Sun Yat-Sen University)
More from the Same Authors
-
2021 : One Million Scenes for Autonomous Driving: ONCE Dataset »
Jiageng Mao · Niu Minzhe · ChenHan Jiang · hanxue liang · Jingheng Chen · Xiaodan Liang · Yamin Li · Chaoqiang Ye · Wei Zhang · Zhenguo Li · Jie Yu · Hang Xu · Chunjing XU -
2021 : Occluded Video Instance Segmentation: Dataset and ICCV 2021 Challenge »
Jiyang Qi · Yan Gao · Yao Hu · Xinggang Wang · Xiaoyu Liu · Xiang Bai · Serge Belongie · Alan Yuille · Philip Torr · Song Bai -
2021 : FFA-IR: Towards an Explainable and Reliable Medical Report Generation Benchmark »
Mingjie Li · Wenjia Cai · Rui Liu · Yuetian Weng · Xiaoyun Zhao · Cong Wang · Xin Chen · Zhong Liu · Caineng Pan · Mengke Li · yingfeng zheng · Yizhi Liu · Flora Salim · Karin Verspoor · Xiaodan Liang · Xiaojun Chang -
2021 : IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning »
Pan Lu · Liang Qiu · Jiaqi Chen · Tanglin Xia · Yizhou Zhao · Wei Zhang · Zhou Yu · Xiaodan Liang · Song-Chun Zhu -
2021 : SODA10M: A Large-Scale 2D Self/Semi-Supervised Object Detection Dataset for Autonomous Driving »
Jianhua Han · Xiwen Liang · Hang Xu · Kai Chen · Lanqing Hong · Jiageng Mao · Chaoqiang Ye · Wei Zhang · Zhenguo Li · Xiaodan Liang · Chunjing XU -
2021 : Theorem-Aware Geometry Problem Solving with Symbolic Reasoning and Theorem Prediction »
Pan Lu · Ran Gong · Shibiao Jiang · Liang Qiu · Siyuan Huang · Xiaodan Liang · Song-Chun Zhu · Ran Gong -
2021 : Towards Diagram Understanding and Cognitive Reasoning in Icon Question Answering »
Pan Lu · Liang Qiu · Jiaqi Chen · Tanglin Xia · Yizhou Zhao · Wei Zhang · Zhou Yu · Xiaodan Liang · Song-Chun Zhu -
2021 : Geometric Question Answering Towards Multimodal Numerical Reasoning »
Jiaqi Chen · Jianheng Tang · Jinghui Qin · Xiaodan Liang · Lingbo Liu · Eric Xing · Liang Lin -
2021 : Are Vision Transformers Always More Robust Than Convolutional Neural Networks? »
Francesco Pinto · Philip Torr · Puneet Dokania -
2021 : Mix-MaxEnt: Improving Accuracy and Uncertainty Estimates of Deterministic Neural Networks »
Francesco Pinto · Harry Yang · Ser Nam Lim · Philip Torr · Puneet Dokania -
2022 Poster: Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning »
Zaiyu Huang · Hanhui Li · Zhenyu Xie · Michael Kampffmeyer · qingling Cai · Xiaodan Liang -
2023 Poster: ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation »
Shuyang Sun · Weijun Wang · Andrew Howard · Qihang Yu · Philip Torr · Liang-Chieh Chen -
2023 Poster: Language Model Tokenizers Introduce Unfairness Between Languages »
Aleksandar Petrov · Emanuele La Malfa · Philip Torr · Adel Bibi -
2023 Poster: Towards More Stable Training of Diffusion Model via Scaling Network Long Skip Connection »
Zhongzhan Huang · Pan Zhou · Shuicheng Yan · Liang Lin -
2023 Poster: Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union »
Zifu Wang · Maxim Berman · Amal Rannen-Triki · Philip Torr · Devis Tuia · Tinne Tuytelaars · Luc V Gool · Jiaqian Yu · Matthew Blaschko -
2023 Poster: RIO: A Benchmark for Reasoning Intention-Oriented Objects in Open Environments »
Mengxue Qu · Yu Wu · Wu Liu · Xiaodan Liang · Jingkuan Song · Yao Zhao · Yunchao Wei -
2023 Poster: Benchmarking Robustness of Adaptation Methods on Pre-trained Vision-Language Models »
Shuo Chen · Jindong Gu · Zhen Han · Yunpu Ma · Philip Torr · Volker Tresp -
2022 Spotlight: Divide and Contrast: Source-free Domain Adaptation via Adaptive Contrastive Learning »
Ziyi Zhang · Weikai Chen · Hui Cheng · Zhen Li · Siyuan Li · Liang Lin · Guanbin Li -
2022 Spotlight: Lightning Talks 4B-3 »
Zicheng Zhang · Mancheng Meng · Antoine Guedon · Yue Wu · Wei Mao · Zaiyu Huang · Peihao Chen · Shizhe Chen · Yongwei Chen · Keqiang Sun · Yi Zhu · chen rui · Hanhui Li · Dongyu Ji · Ziyan Wu · miaomiao Liu · Pascal Monasse · Yu Deng · Shangzhe Wu · Pierre-Louis Guhur · Jiaolong Yang · Kunyang Lin · Makarand Tapaswi · Zhaoyang Huang · Terrence Chen · Jiabao Lei · Jianzhuang Liu · Vincent Lepetit · Zhenyu Xie · Richard I Hartley · Dinggang Shen · Xiaodan Liang · Runhao Zeng · Cordelia Schmid · Michael Kampffmeyer · Mathieu Salzmann · Ning Zhang · Fangyun Wei · Yabin Zhang · Fan Yang · Qifeng Chen · Wei Ke · Quan Wang · Thomas Li · qingling Cai · Kui Jia · Ivan Laptev · Mingkui Tan · Xin Tong · Hongsheng Li · Xiaodan Liang · Chuang Gan -
2022 Spotlight: Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning »
Zaiyu Huang · Hanhui Li · Zhenyu Xie · Michael Kampffmeyer · qingling Cai · Xiaodan Liang -
2022 Spotlight: CoupAlign: Coupling Word-Pixel with Sentence-Mask Alignments for Referring Image Segmentation »
Zicheng Zhang · Yi Zhu · Jianzhuang Liu · Xiaodan Liang · Wei Ke -
2022 Poster: Divide and Contrast: Source-free Domain Adaptation via Adaptive Contrastive Learning »
Ziyi Zhang · Weikai Chen · Hui Cheng · Zhen Li · Siyuan Li · Liang Lin · Guanbin Li -
2022 Poster: Using Mixup as a Regularizer Can Surprisingly Improve Accuracy & Out-of-Distribution Robustness »
Francesco Pinto · Harry Yang · Ser Nam Lim · Philip Torr · Puneet Dokania -
2022 Poster: Learn what matters: cross-domain imitation learning with task-relevant embeddings »
Tim Franzmeyer · Philip Torr · João Henriques -
2022 Poster: Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training Benchmark »
Jiaxi Gu · Xiaojun Meng · Guansong Lu · Lu Hou · Niu Minzhe · Xiaodan Liang · Lewei Yao · Runhui Huang · Wei Zhang · Xin Jiang · Chunjing XU · Hang Xu -
2022 Poster: DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection »
Lewei Yao · Jianhua Han · Youpeng Wen · Xiaodan Liang · Dan Xu · Wei Zhang · Zhenguo Li · Chunjing XU · Hang Xu -
2022 Poster: Make Some Noise: Reliable and Efficient Single-Step Adversarial Training »
Pau de Jorge Aranda · Adel Bibi · Riccardo Volpi · Amartya Sanyal · Philip Torr · Gregory Rogez · Puneet Dokania -
2022 Poster: FedSR: A Simple and Effective Domain Generalization Method for Federated Learning »
A. Tuan Nguyen · Philip Torr · Ser Nam Lim -
2022 Poster: Effective Adaptation in Multi-Task Co-Training for Unified Autonomous Driving »
Xiwen Liang · Yangxin Wu · Jianhua Han · Hang Xu · Chunjing XU · Xiaodan Liang -
2022 Poster: CoupAlign: Coupling Word-Pixel with Sentence-Mask Alignments for Referring Image Segmentation »
Zicheng Zhang · Yi Zhu · Jianzhuang Liu · Xiaodan Liang · Wei Ke -
2021 : Shape-Tailored Deep Neural Networks With PDEs »
Naeemullah Khan · Angira Sharma · Philip Torr · Ganesh Sundaramoorthi -
2021 Workshop: Math AI for Education (MATHAI4ED): Bridging the Gap Between Research and Smart Education »
Pan Lu · Yuhuai Wu · Sean Welleck · Xiaodan Liang · Eric Xing · James McClelland -
2021 Poster: You Never Cluster Alone »
Yuming Shen · Ziyi Shen · Menghan Wang · Jie Qin · Philip Torr · Ling Shao -
2021 Poster: Rethinking the Pruning Criteria for Convolutional Neural Network »
Zhongzhan Huang · Wenqi Shao · Xinjiang Wang · Liang Lin · Ping Luo -
2021 Poster: Looking Beyond Single Images for Contrastive Semantic Segmentation Learning »
FEIHU ZHANG · Philip Torr · Rene Ranftl · Stephan Richter -
2021 Poster: FACMAC: Factored Multi-Agent Centralised Policy Gradients »
Bei Peng · Tabish Rashid · Christian Schroeder de Witt · Pierre-Alexandre Kamienny · Philip Torr · Wendelin Boehmer · Shimon Whiteson -
2021 Poster: Do Different Tracking Tasks Require Different Appearance Models? »
Zhongdao Wang · Hengshuang Zhao · Ya-Li Li · Shengjin Wang · Philip Torr · Luca Bertinetto -
2021 Poster: Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN »
Zhenyu Xie · Zaiyu Huang · Fuwei Zhao · Haoye Dong · Michael Kampffmeyer · Xiaodan Liang -
2021 Poster: A Continuous Mapping For Augmentation Design »
Keyu Tian · Chen Lin · Ser Nam Lim · Wanli Ouyang · Puneet Dokania · Philip Torr -
2021 Poster: Overcoming the Convex Barrier for Simplex Inputs »
Harkirat Singh Behl · M. Pawan Kumar · Philip Torr · Krishnamurthy Dvijotham -
2020 Poster: STEER : Simple Temporal Regularization For Neural ODE »
Arnab Ghosh · Harkirat Singh Behl · Emilien Dupont · Philip Torr · Vinay Namboodiri -
2020 Poster: Calibrating Deep Neural Networks using Focal Loss »
Jishnu Mukhoti · Viveka Kulharia · Amartya Sanyal · Stuart Golodetz · Philip Torr · Puneet Dokania -
2020 Poster: Lightweight Generative Adversarial Networks for Text-Guided Image Manipulation »
Bowen Li · Xiaojuan Qi · Philip Torr · Thomas Lukasiewicz -
2020 Poster: AutoSync: Learning to Synchronize for Data-Parallel Distributed Deep Learning »
Hao Zhang · Yuan Li · Zhijie Deng · Xiaodan Liang · Lawrence Carin · Eric Xing -
2020 Poster: Continual Learning in Low-rank Orthogonal Subspaces »
Arslan Chaudhry · Naeemullah Khan · Puneet Dokania · Philip Torr -
2020 Poster: Auto-Panoptic: Cooperative Multi-Component Architecture Search for Panoptic Segmentation »
Yangxin Wu · Gengwei Zhang · Hang Xu · Xiaodan Liang · Liang Lin -
2020 Poster: Towards Interpretable Natural Language Understanding with Explanations as Latent Variables »
Wangchunshu Zhou · Jinyi Hu · Hanlin Zhang · Xiaodan Liang · Maosong Sun · Chenyan Xiong · Jian Tang -
2019 : Coffee + Posters »
Changhao Chen · Nils Gählert · Edouard Leurent · Johannes Lehner · Apratim Bhattacharyya · Harkirat Singh Behl · Teck Yian Lim · Shiho Kim · Jelena Novosel · Błażej Osiński · Arindam Das · Ruobing Shen · Jeffrey Hawke · Joachim Sicking · Babak Shahian Jahromi · Theja Tulabandhula · Claudio Michaelis · Evgenia Rusak · WENHANG BAO · Hazem Rashed · JP Chen · Amin Ansari · Jaekwang Cha · Mohamed Zahran · Daniele Reda · Jinhyuk Kim · Kim Dohyun · Ho Suk · Junekyo Jhung · Alexander Kister · Matthias Fahrland · Adam Jakubowski · Piotr Miłoś · Jean Mercat · Bruno Arsenali · Silviu Homoceanu · Xiao-Yang Liu · Philip Torr · Ahmad El Sallab · Ibrahim Sobh · Anurag Arnab · Krzysztof Galias -
2019 Poster: Multi-Agent Common Knowledge Reinforcement Learning »
Christian Schroeder de Witt · Jakob Foerster · Gregory Farquhar · Philip Torr · Wendelin Boehmer · Shimon Whiteson -
2019 Poster: Heterogeneous Graph Learning for Visual Commonsense Reasoning »
Weijiang Yu · Jingwen Zhou · Weihao Yu · Xiaodan Liang · Nong Xiao -
2019 Spotlight: Heterogeneous Graph Learning for Visual Commonsense Reasoning »
Weijiang Yu · Jingwen Zhou · Weihao Yu · Xiaodan Liang · Nong Xiao -
2019 Poster: Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model »
Atilim Gunes Baydin · Lei Shao · Wahid Bhimji · Lukas Heinrich · Saeid Naderiparizi · Andreas Munk · Jialin Liu · Bradley Gram-Hansen · Gilles Louppe · Lawrence Meadows · Philip Torr · Victor Lee · Kyle Cranmer · Mr. Prabhat · Frank Wood -
2019 Poster: Controllable Text-to-Image Generation »
Bowen Li · Xiaojuan Qi · Thomas Lukasiewicz · Philip Torr -
2018 Poster: A Unified View of Piecewise Linear Neural Network Verification »
Rudy Bunel · Ilker Turkaslan · Philip Torr · Pushmeet Kohli · Pawan K Mudigonda -
2018 Poster: Symbolic Graph Reasoning Meets Convolutions »
Xiaodan Liang · Zhiting Hu · Hao Zhang · Liang Lin · Eric Xing -
2018 Poster: Deep Generative Models with Learnable Knowledge Constraints »
Zhiting Hu · Zichao Yang · Russ Salakhutdinov · LIANHUI Qin · Xiaodan Liang · Haoye Dong · Eric Xing -
2018 Poster: Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation »
Yuan Li · Xiaodan Liang · Zhiting Hu · Eric Xing -
2018 Poster: Hybrid Knowledge Routed Modules for Large-scale Object Detection »
ChenHan Jiang · Hang Xu · Xiaodan Liang · Liang Lin -
2018 Poster: Kalman Normalization: Normalizing Internal Representations Across Network Layers »
Guangrun Wang · jiefeng peng · Ping Luo · Xinjiang Wang · Liang Lin -
2018 Poster: Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis »
Haoye Dong · Xiaodan Liang · Ke Gong · Hanjiang Lai · Jia Zhu · Jian Yin -
2017 Poster: Structured Generative Adversarial Networks »
Zhijie Deng · Hao Zhang · Xiaodan Liang · Luona Yang · Shizhen Xu · Jun Zhu · Eric Xing -
2017 Poster: Learning Disentangled Representations with Semi-Supervised Deep Generative Models »
Siddharth Narayanaswamy · Brooks Paige · Jan-Willem van de Meent · Alban Desmaison · Noah Goodman · Pushmeet Kohli · Frank Wood · Philip Torr -
2016 Poster: Adaptive Neural Compilation »
Rudy Bunel · Alban Desmaison · Pawan K Mudigonda · Pushmeet Kohli · Philip Torr -
2016 Poster: Learning feed-forward one-shot learners »
Luca Bertinetto · João Henriques · Jack Valmadre · Philip Torr · Andrea Vedaldi -
2016 Poster: Tree-Structured Reinforcement Learning for Sequential Object Localization »
Zequn Jie · Xiaodan Liang · Jiashi Feng · Xiaojie Jin · Wen Lu · Shuicheng Yan -
2014 Poster: Deep Joint Task Learning for Generic Object Extraction »
Xiaolong Wang · Liliang Zhang · Liang Lin · Zhujin Liang · Wangmeng Zuo -
2013 Poster: Higher Order Priors for Joint Intrinsic Image, Objects, and Attributes Estimation »
Vibhav Vineet · Carsten Rother · Philip Torr -
2011 Poster: Learning Anchor Planes for Classification »
Ziming Zhang · Lubor Ladicky · Philip Torr · Amir Saffari -
2011 Demonstration: Online structured-output learning for real-time object tracking and detection »
Sam Hare · Amir Saffari · Philip Torr -
2008 Poster: Improved Moves for Truncated Convex Models »
Pawan K Mudigonda · Philip Torr -
2008 Spotlight: Improved Moves for Truncated Convex Models »
Pawan K Mudigonda · Philip Torr -
2007 Oral: An Analysis of Convex Relaxations for MAP Estimation »
Pawan K Mudigonda · Vladimir Kolmogorov · Philip Torr -
2007 Poster: An Analysis of Convex Relaxations for MAP Estimation »
Pawan K Mudigonda · Vladimir Kolmogorov · Philip Torr