Search Results for author: Tomas Hodan

Found 13 papers, 4 papers with code

BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objects

no code implementations25 Feb 2023 Martin Sundermeyer, Tomas Hodan, Yann Labbe, Gu Wang, Eric Brachmann, Bertram Drost, Carsten Rother, Jiri Matas

In 2022, we witnessed another significant improvement in the pose estimation accuracy -- the state of the art, which was 56. 9 AR$_C$ in 2019 (Vidal et al.) and 69. 8 AR$_C$ in 2020 (CosyPose), moved to new heights of 83. 7 AR$_C$ (GDRNPP).

2D object detection 6D Pose Estimation using RGB +2

In-Hand 3D Object Scanning from an RGB Sequence

no code implementations28 Nov 2022 Shreyas Hampali, Tomas Hodan, Luan Tran, Lingni Ma, Cem Keskin, Vincent Lepetit

As global optimization over all the shape and pose parameters is prone to fail without coarse-level initialization of the poses, we propose an incremental approach which starts by splitting the sequence into carefully selected overlapping segments within which the optimization is likely to succeed.

UmeTrack: Unified multi-view end-to-end hand tracking for VR

no code implementations31 Oct 2022 Shangchen Han, Po-Chen Wu, Yubo Zhang, Beibei Liu, Linguang Zhang, Zheng Wang, Weiguang Si, Peizhao Zhang, Yujun Cai, Tomas Hodan, Randi Cabezas, Luan Tran, Muzaffer Akbay, Tsz-Ho Yu, Cem Keskin, Robert Wang

In this paper, we present a unified end-to-end differentiable framework for multi-view, multi-frame hand tracking that directly predicts 3D hand pose in world space.

Neural Correspondence Field for Object Pose Estimation

no code implementations30 Jul 2022 Lin Huang, Tomas Hodan, Lingni Ma, Linguang Zhang, Luan Tran, Christopher Twigg, Po-Chen Wu, Junsong Yuan, Cem Keskin, Robert Wang

Unlike classical correspondence-based methods which predict 3D object coordinates at pixels of the input image, the proposed method predicts 3D object coordinates at 3D query points sampled in the camera frustum.

3D Reconstruction Pose Estimation

Pose Estimation of Specific Rigid Objects

no code implementations30 Dec 2021 Tomas Hodan

Second, we present HashMatch, an RGB-D method that slides a window over the input image and searches for a match against templates, which are pre-generated by rendering 3D object models in different orientations.

6D Pose Estimation using RGB Autonomous Driving

BOP Challenge 2020 on 6D Object Localization

4 code implementations15 Sep 2020 Tomas Hodan, Martin Sundermeyer, Bertram Drost, Yann Labbe, Eric Brachmann, Frank Michel, Carsten Rother, Jiri Matas

This paper presents the evaluation methodology, datasets, and results of the BOP Challenge 2020, the third in a series of public competitions organized with the goal to capture the status quo in the field of 6D object pose estimation from an RGB-D image.

6D Pose Estimation 6D Pose Estimation using RGB +3

Learning Surrogates via Deep Embedding

no code implementations ECCV 2020 Yash Patel, Tomas Hodan, Jiri Matas

The effectiveness of the proposed technique is demonstrated in a post-tuning setup, where a trained model is tuned using the learned surrogate.

Scene Text Recognition

EPOS: Estimating 6D Pose of Objects with Symmetries

1 code implementation CVPR 2020 Tomas Hodan, Daniel Barath, Jiri Matas

A data-dependent number of corresponding 3D locations is selected per pixel, and poses of possibly multiple object instances are estimated using a robust and efficient variant of the PnP-RANSAC algorithm.

6D Pose Estimation 6D Pose Estimation using RGB +1

Photorealistic Image Synthesis for Object Instance Detection

no code implementations9 Feb 2019 Tomas Hodan, Vibhav Vineet, Ran Gal, Emanuel Shalev, Jon Hanzelka, Treb Connell, Pedro Urbina, Sudipta N. Sinha, Brian Guenter

We present an approach to synthesize highly photorealistic images of 3D object models, which we use to train a convolutional neural network for detecting the objects in real images.

6D Pose Estimation 6D Pose Estimation using RGB +2

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