Tomas Jakab

According to our database, Tomas Jakab authored at least 14 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

DreamHOI: Subject-Driven Generation of 3D Human-Object Interactions with Diffusion Priors.

Thomas Hanwen Zhu, Ruining Li, Tomas Jakab

CoRR, 2024

DreamBeast: Distilling 3D Fantastical Animals with Part-Aware Knowledge Transfer.

Runjia Li, Junlin Han, Luke Melas-Kyriazi, Chunyi Sun, Zhaochong An, Zhongrui Gui, Shuyang Sun, Philip Torr, Tomas Jakab

CoRR, 2024

Scene-Conditional 3D Object Stylization and Composition.

Jinghao Zhou, Tomas Jakab, Philip Torr, Christian Rupprecht

Proceedings of the Computer Vision - ECCV 2024, 2024

Instant Uncertainty Calibration of NeRFs Using a Meta-calibrator.

Niki Amini-Naieni, Tomas Jakab, Andrea Vedaldi, Ronald Clark

Proceedings of the Computer Vision - ECCV 2024, 2024

Learning the 3D Fauna of the Web.

Zizhang Li, Dor Litvak, Ruining Li, Yunzhi Zhang, Tomas Jakab, Christian Rupprecht, Shangzhe Wu, Andrea Vedaldi, Jiajun Wu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Farm3D: Learning Articulated 3D Animals by Distilling 2D Diffusion.

Tomas Jakab, Ruining Li, Shangzhe Wu, Christian Rupprecht, Andrea Vedaldi

Proceedings of the International Conference on 3D Vision, 2024

2023

DOVE: Learning Deformable 3D Objects by Watching Videos.

Shangzhe Wu, Tomas Jakab, Christian Rupprecht, Andrea Vedaldi

Int. J. Comput. Vis., October, 2023

Calibrated Uncertainties for Neural Radiance Fields.

Niki Amini-Naieni, Tomas Jakab, Andrea Vedaldi, Ronald Clark

CoRR, 2023

MagicPony: Learning Articulated 3D Animals in the Wild.

Shangzhe Wu, Ruining Li, Tomas Jakab, Christian Rupprecht, Andrea Vedaldi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2021

KeypointDeformer: Unsupervised 3D Keypoint Discovery for Shape Control.

Tomas Jakab, Richard Tucker, Ameesh Makadia, Jiajun Wu, Noah Snavely, Angjoo Kanazawa

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Self-Supervised Learning of Interpretable Keypoints From Unlabelled Videos.

Tomas Jakab, Ankush Gupta, Hakan Bilen, Andrea Vedaldi

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Learning Landmarks from Unaligned Data using Image Translation.

Tomas Jakab, Ankush Gupta, Hakan Bilen, Andrea Vedaldi

CoRR, 2019

2018

Conditional Image Generation for Learning the Structure of Visual Objects.

Tomas Jakab, Ankush Gupta, Hakan Bilen, Andrea Vedaldi

CoRR, 2018

Unsupervised Learning of Object Landmarks through Conditional Image Generation.

Tomas Jakab, Ankush Gupta, Hakan Bilen, Andrea Vedaldi

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018