# Recent Advances in 3D Object and Hand Pose Estimation

arXiv: https://arxiv.org/abs/2006.05927 · HTML: https://mlsanity.com/paper/2006.05927/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Jun 2020.

## Built on by (most cited first, 9 of 9)

- [InterCap: Joint Markerless 3D Tracking of Humans and Objects in Interaction](https://mlsanity.com/paper/2209.12354/) (2022)
- [Towards unconstrained joint hand-object reconstruction from RGB videos](https://mlsanity.com/paper/2108.07044/) (2021)
- [gSDF: Geometry-Driven Signed Distance Functions for 3D Hand-Object Reconstruction](https://mlsanity.com/paper/2304.11970/) (2023)
- [Efficient Annotation and Learning for 3D Hand Pose Estimation: A Survey](https://mlsanity.com/paper/2206.02257/) (2022)
- [EvHandPose: Event-based 3D Hand Pose Estimation with Sparse Supervision](https://mlsanity.com/paper/2303.02862/) (2023)
- [HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields](https://mlsanity.com/paper/2402.17062/) (2024)
- [DISP6D: Disentangled Implicit Shape and Pose Learning for Scalable 6D Pose Estimation](https://mlsanity.com/paper/2107.12549/) (2021)
- [HORT: Monocular Hand-held Objects Reconstruction with Transformers](https://mlsanity.com/paper/2503.21313/) (2025)
- [Temporally Consistent Object 6D Pose Estimation for Robot Control](https://mlsanity.com/paper/2605.02708/) (2026)

## Abstract (arXiv)

3D object and hand pose estimation have huge potentials for Augmented Reality, to enable tangible interfaces, natural interfaces, and blurring the boundaries between the real and virtual worlds. In this chapter, we present the recent developments for 3D object and hand pose estimation using cameras, and discuss their abilities and limitations and the possible future development of the field.