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20152025
most citedLifting from the Deep: Convolutional 3D Pose Estimation from a Single Image

546 citations · 1.1k across the 29 of their papers we have counts for

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Showing 2018Show all

5 papers · 1 filter

cs.CV2018★ 1 cited

3D Pick & Mix: Object Part Blending in Joint Shape and Image Manifolds

Adrian Penate-Sanchez, Lourdes Agapito

We present 3D Pick & Mix, a new 3D shape retrieval system that provides users with a new level of freedom to explore 3D shape and Internet image collections by introducing the abil…

cs.CV2018★ 3 cited

Rethinking Pose in 3D: Multi-stage Refinement and Recovery for Markerless Motion Capture

Denis Tome, Matteo Toso, Lourdes Agapito +1

We propose a CNN-based approach for multi-camera markerless motion capture of the human body. Unlike existing methods that first perform pose estimation on individual cameras and g…

cs.CV2018

MaskFusion: Real-Time Recognition, Tracking and Reconstruction of Multiple Moving Objects

Martin Rünz, Maud Buffier, Lourdes Agapito

We present MaskFusion, a real-time, object-aware, semantic and dynamic RGB-D SLAM system that goes beyond traditional systems which output a purely geometric map of a static scene.…

stat.ML2018★ 6 cited

Training VAEs Under Structured Residuals

Gara Dorta, Sara Vicente, Lourdes Agapito +2

Variational auto-encoders (VAEs) are a popular and powerful deep generative model. Previous works on VAEs have assumed a factorized likelihood model, whereby the output uncertainty…

stat.ML2018

Structured Uncertainty Prediction Networks

Gara Dorta, Sara Vicente, Lourdes Agapito +2

This paper is the first work to propose a network to predict a structured uncertainty distribution for a synthesized image. Previous approaches have been mostly limited to predicti…