3 citations · 4 across the 5 of their papers we have counts for
7 papers · 1 filter
A Simple and Powerful Global Optimization for Unsupervised Video Object Segmentation
Georgy Ponimatkin, Nermin Samet, Yang Xiao +3
We propose a simple, yet powerful approach for unsupervised object segmentation in videos. We introduce an objective function whose minimum represents the mask of the main salient…
WiCV 2021: The Eighth Women In Computer Vision Workshop
Arushi Goel, Niveditha Kalavakonda, Nour Karessli +5
In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2021, organized alongside the virtual CVPR 2021. It provides a voice to a minority (female) group…
HPRNet: Hierarchical Point Regression for Whole-Body Human Pose Estimation
Nermin Samet, Emre Akbas
In this paper, we present a new bottom-up one-stage method for whole-body pose estimation, which we call "hierarchical point regression," or HPRNet for short. In standard body pose…
Adversarial Segmentation Loss for Sketch Colorization
Samet Hicsonmez, Nermin Samet, Emre Akbas +1
We introduce a new method for generating color images from sketches or edge maps. Current methods either require some form of additional user-guidance or are limited to the "paired…
Reducing Label Noise in Anchor-Free Object Detection
Nermin Samet, Samet Hicsonmez, Emre Akbas
Current anchor-free object detectors label all the features that spatially fall inside a predefined central region of a ground-truth box as positive. This approach causes label noi…
HoughNet: Integrating near and long-range evidence for bottom-up object detection
Nermin Samet, Samet Hicsonmez, Emre Akbas
This paper presents HoughNet, a one-stage, anchor-free, voting-based, bottom-up object detection method. Inspired by the Generalized Hough Transform, HoughNet determines the presen…