# GANerated Hands for Real-time 3D Hand Tracking from Monocular RGB

arXiv: https://arxiv.org/abs/1712.01057 · HTML: https://mlsanity.com/paper/1712.01057/

## Key facts

- Cited by 147 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Dec 2017.

## Built on by (most cited first, 30 of 147)

- [DexYCB: A Benchmark for Capturing Hand Grasping of Objects](https://mlsanity.com/paper/2104.04631/) (2021)
- [ARCTIC: A Dataset for Dexterous Bimanual Hand-Object Manipulation](https://mlsanity.com/paper/2204.13662/) (2022)
- [Fake It Till You Make It: Face analysis in the wild using synthetic data alone](https://mlsanity.com/paper/2109.15102/) (2021)
- [Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time](https://mlsanity.com/paper/2106.05266/) (2021)
- [ContactOpt: Optimizing Contact to Improve Grasps](https://mlsanity.com/paper/2104.07267/) (2021)
- [Collaborative Regression of Expressive Bodies using Moderation](https://mlsanity.com/paper/2105.05301/) (2021)
- [Affordance Diffusion: Synthesizing Hand-Object Interactions](https://mlsanity.com/paper/2303.12538/) (2023)
- [Neural Actor: Neural Free-view Synthesis of Human Actors with Pose Control](https://mlsanity.com/paper/2106.02019/) (2021)
- [Recovering 3D Human Mesh from Monocular Images: A Survey](https://mlsanity.com/paper/2203.01923/) (2022)
- [What's in your hands? 3D Reconstruction of Generic Objects in Hands](https://mlsanity.com/paper/2204.07153/) (2022)
- [Interacting Attention Graph for Single Image Two-Hand Reconstruction](https://mlsanity.com/paper/2203.09364/) (2022)
- [CAPTRA: CAtegory-level Pose Tracking for Rigid and Articulated Objects from Point Clouds](https://mlsanity.com/paper/2104.03437/) (2021)
- [An Outlook into the Future of Egocentric Vision](https://mlsanity.com/paper/2308.07123/) (2023)
- [Fine-Grained Egocentric Hand-Object Segmentation: Dataset, Model, and Applications](https://mlsanity.com/paper/2208.03826/) (2022)
- [HOLD: Category-agnostic 3D Reconstruction of Interacting Hands and Objects from Video](https://mlsanity.com/paper/2311.18448/) (2023)
- [ArtiBoost: Boosting Articulated 3D Hand-Object Pose Estimation via Online Exploration and Synthesis](https://mlsanity.com/paper/2109.05488/) (2021)
- [MobRecon: Mobile-Friendly Hand Mesh Reconstruction from Monocular Image](https://mlsanity.com/paper/2112.02753/) (2021)
- [Real-time Pose and Shape Reconstruction of Two Interacting Hands With a Single Depth Camera](https://mlsanity.com/paper/2106.08059/) (2021)
- [AlignSDF: Pose-Aligned Signed Distance Fields for Hand-Object Reconstruction](https://mlsanity.com/paper/2207.12909/) (2022)
- [Towards unconstrained joint hand-object reconstruction from RGB videos](https://mlsanity.com/paper/2108.07044/) (2021)
- [ParaHome: Parameterizing Everyday Home Activities Towards 3D Generative Modeling of Human-Object Interactions](https://mlsanity.com/paper/2401.10232/) (2024)
- [Collaborative Learning for Hand and Object Reconstruction with Attention-guided Graph Convolution](https://mlsanity.com/paper/2204.13062/) (2022)
- [A Skeleton-Driven Neural Occupancy Representation for Articulated Hands](https://mlsanity.com/paper/2109.11399/) (2021)
- [UmeTrack: Unified multi-view end-to-end hand tracking for VR](https://mlsanity.com/paper/2211.00099/) (2022)
- [gSDF: Geometry-Driven Signed Distance Functions for 3D Hand-Object Reconstruction](https://mlsanity.com/paper/2304.11970/) (2023)
- [Towards Accurate Alignment in Real-time 3D Hand-Mesh Reconstruction](https://mlsanity.com/paper/2109.01723/) (2021)
- [Learning to Disambiguate Strongly Interacting Hands via Probabilistic Per-pixel Part Segmentation](https://mlsanity.com/paper/2107.00434/) (2021)
- [Pose for Everything: Towards Category-Agnostic Pose Estimation](https://mlsanity.com/paper/2207.10387/) (2022)
- [EasyHOI: Unleashing the Power of Large Models for Reconstructing Hand-Object Interactions in the Wild](https://mlsanity.com/paper/2411.14280/) (2024)
- [Hierarchical Temporal Transformer for 3D Hand Pose Estimation and Action Recognition from Egocentric RGB Videos](https://mlsanity.com/paper/2209.09484/) (2022)

## Abstract (arXiv)

We address the highly challenging problem of real-time 3D hand tracking based on a monocular RGB-only sequence. Our tracking method combines a convolutional neural network with a kinematic 3D hand model, such that it generalizes well to unseen data, is robust to occlusions and varying camera viewpoints, and leads to anatomically plausible as well as temporally smooth hand motions. For training our CNN we propose a novel approach for the synthetic generation of training data that is based on a geometrically consistent image-to-image translation network. To be more specific, we use a neural network that translates synthetic images to "real" images, such that the so-generated images follow the same statistical distribution as real-world hand images. For training this translation network we combine an adversarial loss and a cycle-consistency loss with a geometric consistency loss in order to preserve geometric properties (such as hand pose) during translation. We demonstrate that our hand tracking system outperforms the current state-of-the-art on challenging RGB-only footage.