79 citations · 174 across the 39 of their papers we have counts for
7 papers · 1 filter
Mask-aware IoU for Anchor Assignment in Real-time Instance Segmentation
Kemal Oksuz, Baris Can Cam, Fehmi Kahraman +3
This paper presents Mask-aware Intersection-over-Union (maIoU) for assigning anchor boxes as positives and negatives during training of instance segmentation methods. Unlike conven…
Rank & Sort Loss for Object Detection and Instance Segmentation
Kemal Oksuz, Baris Can Cam, Emre Akbas +1
We propose Rank & Sort (RS) Loss, a ranking-based loss function to train deep object detection and instance segmentation methods (i.e. visual detectors). RS Loss supervises the cla…
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…
HoughNet: Integrating near and long-range evidence for visual 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…
Just Noticeable Difference for Machine Perception and Generation of Regularized Adversarial Images with Minimal Perturbation
Adil Kaan Akan, Emre Akbas, Fatos T. Yarman Vural
In this study, we introduce a measure for machine perception, inspired by the concept of Just Noticeable Difference (JND) of human perception. Based on this measure, we suggest an…
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…