Canonical 3D Deformer Maps: Unifying parametric and non-parametric
methods for dense weakly-supervised category reconstruction

Canonical 3D Deformer Maps: Unifying parametric and non-parametric methods for dense weakly-supervised category reconstruction

28 August 2020

Roman Shapovalov

Andrea Vedaldi

Papers citing "Canonical 3D Deformer Maps: Unifying parametric and non-parametric methods for dense weakly-supervised category reconstruction"

5 / 5 papers shown

Title
Canonical Fields: Self-Supervised Learning of Pose-Canonicalized Neural Fields Rohith Agaram Shaurya Dewan Rahul Sajnani A. Poulenard Madhava Krishna Srinath Sridhar 41 6 0 05 Dec 2022
Virtual Correspondence: Humans as a Cue for Extreme-View Geometry Wei-Chiu Ma A. Yang Shenlong Wang R. Urtasun Antonio Torralba 53 26 0 16 Jun 2022
To The Point: Correspondence-driven monocular 3D category reconstruction Filippos Kokkinos Iasonas Kokkinos 3DH 3DPC 29 24 0 10 Jun 2021
CoCoNets: Continuous Contrastive 3D Scene Representations Shamit Lal Mihir Prabhudesai Ishita Mediratta Adam W. Harley Katerina Fragkiadaki SSL 3DH 3DPC 36 25 0 08 Apr 2021
DensePose: Dense Human Pose Estimation In The Wild R. Güler Natalia Neverova Iasonas Kokkinos 3DH 211 1,386 0 01 Feb 2018