11 citations · 11 across the 3 of their papers we have counts for
10 papers · 1 filter
Multi-person Implicit Reconstruction from a Single Image
Armin Mustafa, Akin Caliskan, Lourdes Agapito +1
We present a new end-to-end learning framework to obtain detailed and spatially coherent reconstructions of multiple people from a single image. Existing multi-person methods suffe…
Temporal Consistency Loss for High Resolution Textured and Clothed 3DHuman Reconstruction from Monocular Video
Akin Caliskan, Armin Mustafa, Adrian Hilton
We present a novel method to learn temporally consistent 3D reconstruction of clothed people from a monocular video. Recent methods for 3D human reconstruction from monocular video…
Multi-View Consistency Loss for Improved Single-Image 3D Reconstruction of Clothed People
Akin Caliskan, Armin Mustafa, Evren Imre +1
We present a novel method to improve the accuracy of the 3D reconstruction of clothed human shape from a single image. Recent work has introduced volumetric, implicit and model-bas…
RealMonoDepth: Self-Supervised Monocular Depth Estimation for General Scenes
Mertalp Ocal, Armin Mustafa
We present a generalised self-supervised learning approach for monocular estimation of the real depth across scenes with diverse depth ranges from 1--100s of meters. Existing super…
Learning Dense Wide Baseline Stereo Matching for People
Akin Caliskan, Armin Mustafa, Evren Imre +1
Existing methods for stereo work on narrow baseline image pairs giving limited performance between wide baseline views. This paper proposes a framework to learn and estimate dense…
A*3D Dataset: Towards Autonomous Driving in Challenging Environments
Quang-Hieu Pham, Pierre Sevestre, Ramanpreet Singh Pahwa +6
With the increasing global popularity of self-driving cars, there is an immediate need for challenging real-world datasets for benchmarking and training various computer vision tas…