5 papers · 1 filter
DepthCues: Evaluating Monocular Depth Perception in Large Vision Models
Duolikun Danier, Mehmet Aygün, Changjian Li +2
Large-scale pre-trained vision models are becoming increasingly prevalent, offering expressive and generalizable visual representations that benefit various downstream tasks. Recen…
Enhancing 2D Representation Learning with a 3D Prior
Mehmet Aygün, Prithviraj Dhar, Zhicheng Yan +2
Learning robust and effective representations of visual data is a fundamental task in computer vision. Traditionally, this is achieved by training models with labeled data which ca…
SAOR: Single-View Articulated Object Reconstruction
Mehmet Aygün, Oisin Mac Aodha
We introduce SAOR, a novel approach for estimating the 3D shape, texture, and viewpoint of an articulated object from a single image captured in the wild. Unlike prior approaches t…
Exploiting Convolution Filter Patterns for Transfer Learning
Mehmet Aygün, Yusuf Aytar, Hazım Kemal Ekenel
In this paper, we introduce a new regularization technique for transfer learning. The aim of the proposed approach is to capture statistical relationships among convolution filters…
Apparent Age Estimation Using Ensemble of Deep Learning Models
Refik Can Malli, Mehmet Aygun, Hazim Kemal Ekenel
In this paper, we address the problem of apparent age estimation. Different from estimating the real age of individuals, in which each face image has a single age label, in this pr…