Garment Reconstruction
7 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Garment Reconstruction
Most implemented papers
Deep Fashion3D: A Dataset and Benchmark for 3D Garment Reconstruction from Single Images
ZhengZerong/DeepHuman
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ECCV 2020
High-fidelity clothing reconstruction is the key to achieving photorealism in a wide range of applications including human digitization, virtual try-on, etc.
Learning Anchored Unsigned Distance Functions with Gradient Direction Alignment for Single-view Garment Reconstruction
zhaofang0627/anchorudf
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ICCV 2021
While single-view 3D reconstruction has made significant progress benefiting from deep shape representations in recent years, garment reconstruction is still not solved well due to open surfaces, diverse topologies and complex geometric details.
3D Human Texture Estimation from a Single Image with Transformers
xuxy09/texformer
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ICCV 2021
We propose a Transformer-based framework for 3D human texture estimation from a single image.
Garment4D: Garment Reconstruction from Point Cloud Sequences
hongfz16/garment4d
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NeurIPS 2021
The main challenges are two-fold: 1) effective 3D feature learning for fine details, and 2) capture of garment dynamics caused by the interaction between garments and the human body, especially for loose garments like skirts.
DIG: Draping Implicit Garment over the Human Body
liren2515/dig
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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 differentiable.
REC-MV: REconstructing 3D Dynamic Cloth from Monocular Videos
gap-lab-cuhk-sz/rec-mv
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CVPR 2023
To address the above limitations, in this paper, we formulate this task as an optimization problem of 3D garment feature curves and surface reconstruction from monocular video.
Towards Garment Sewing Pattern Reconstruction from a Single Image
In this work, we explore the challenging problem of recovering garment sewing patterns from daily photos for augmenting these applications.
