64 citations · 104 across the 6 of their papers we have counts for
6 papers
MeshPose: Unifying DensePose and 3D Body Mesh reconstruction
Eric-Tuan Lê, Antonis Kakolyris, Petros Koutras +5
DensePose provides a pixel-accurate association of images with 3D mesh coordinates, but does not provide a 3D mesh, while Human Mesh Reconstruction (HMR) systems have high 2D repro…
Deep, Dense, and Low-Rank Gaussian Conditional Random Fields
Siddhartha Chandra, Iasonas Kokkinos
In this work we introduce a fully-connected graph structure in the Deep Gaussian Conditional Random Field (G-CRF) model. For this we express the pairwise interactions between pixel…
UberNet: Training a `Universal' Convolutional Neural Network for Low-, Mid-, and High-Level Vision using Diverse Datasets and Limited Memory
Iasonas Kokkinos
In this work we introduce a convolutional neural network (CNN) that jointly handles low-, mid-, and high-level vision tasks in a unified architecture that is trained end-to-end. Su…
Prior-based Coregistration and Cosegmentation
Mahsa Shakeri, Enzo Ferrante, Stavros Tsogkas +4
We propose a modular and scalable framework for dense coregistration and cosegmentation with two key characteristics: first, we substitute ground truth data with the semantic map o…
Fracking Deep Convolutional Image Descriptors
Edgar Simo-Serra, Eduard Trulls, Luis Ferraz +2
In this paper we propose a novel framework for learning local image descriptors in a discriminative manner. For this purpose we explore a siamese architecture of Deep Convolutional…
Untangling Local and Global Deformations in Deep Convolutional Networks for Image Classification and Sliding Window Detection
George Papandreou, Iasonas Kokkinos, Pierre-André Savalle
Deep Convolutional Neural Networks (DCNNs) commonly use generic `max-pooling' (MP) layers to extract deformation-invariant features, but we argue in favor of a more refined treatme…