Search Results for author: Emre Akbas

Found 19 papers, 18 papers with code

Mask-aware IoU for Anchor Assignment in Real-time Instance Segmentation

1 code implementation19 Oct 2021 Kemal Oksuz, Baris Can Cam, Fehmi Kahraman, Zeynep Sonat Baltaci, Sinan Kalkan, Emre Akbas

We present the effectiveness of maIoU on a state-of-the-art (SOTA) assigner, ATSS, by replacing IoU operation by our maIoU and training YOLACT, a SOTA real-time instance segmentation method.

Real-time Instance Segmentation Semantic Segmentation

Rank & Sort Loss for Object Detection and Instance Segmentation

2 code implementations ICCV 2021 Kemal Oksuz, Baris Can Cam, Emre Akbas, Sinan Kalkan

RS Loss supervises the classifier, a sub-network of these methods, to rank each positive above all negatives as well as to sort positives among themselves with respect to (wrt.)

Instance Segmentation Object Detection +1

HPRNet: Hierarchical Point Regression for Whole-Body Human Pose Estimation

1 code implementation8 Jun 2021 Nermin Samet, Emre Akbas

Differently, in whole-body pose estimation, the locations of fine-grained keypoints (68 on face, 21 on each hand and 3 on each foot) are estimated as well, which creates a scale variance problem that needs to be addressed.

Face Detection Facial Landmark Detection +4

HoughNet: Integrating near and long-range evidence for visual detection

3 code implementations14 Apr 2021 Nermin Samet, Samet Hicsonmez, Emre Akbas

This paper presents HoughNet, a one-stage, anchor-free, voting-based, bottom-up object detection method.

3D Object Detection Image Generation +4

A Deeper Look into Convolutions via Pruning

1 code implementation4 Feb 2021 Ilke Cugu, Emre Akbas

Convolutional neural networks (CNNs) are able to attain better visual recognition performance than fully connected neural networks despite having much less parameters due to their parameter sharing principle.

Image Classification

One Metric to Measure them All: Localisation Recall Precision (LRP) for Evaluating Visual Detection Tasks

1 code implementation21 Nov 2020 Kemal Oksuz, Baris Can Cam, Sinan Kalkan, Emre Akbas

Panoptic Quality (PQ), a measure proposed for evaluating panoptic segmentation (Kirillov et al., 2019), does not suffer from these limitations but is limited to panoptic segmentation.

Instance Segmentation Keypoint Detection +3

A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object Detection

2 code implementations NeurIPS 2020 Kemal Oksuz, Baris Can Cam, Emre Akbas, Sinan Kalkan

We propose average Localisation-Recall-Precision (aLRP), a unified, bounded, balanced and ranking-based loss function for both classification and localisation tasks in object detection.

Classification General Classification +1

Reducing Label Noise in Anchor-Free Object Detection

1 code implementation BMVC 2020 Nermin Samet, Samet Hicsonmez, Emre Akbas

In this paper, we propose a new labeling strategy aimed to reduce the label noise in anchor-free detectors.

Small Object Detection

HoughNet: Integrating near and long-range evidence for bottom-up object detection

2 code implementations ECCV 2020 Nermin Samet, Samet Hicsonmez, Emre Akbas

We further validate the effectiveness of our proposal in another task, namely, "labels to photo" image generation by integrating the voting module of HoughNet to two different GAN models and showing that the accuracy is significantly improved in both cases.

Image Generation Object Detection

GANILLA: Generative Adversarial Networks for Image to Illustration Translation

4 code implementations13 Feb 2020 Samet Hicsonmez, Nermin Samet, Emre Akbas, Pinar Duygulu

To address this problem, we propose a new framework for the quantitative evaluation of image-to-illustration models, where both content and style are taken into account using separate classifiers.

Image-to-Image Translation Translation

Generating Positive Bounding Boxes for Balanced Training of Object Detectors

1 code implementation21 Sep 2019 Kemal Oksuz, Baris Can Cam, Emre Akbas, Sinan Kalkan

Using our generator as an analysis tool, we show that (i) IoU imbalance has an adverse effect on performance, (ii) hard positive example mining improves the performance only for certain input IoU distributions, and (iii) the imbalance among the foreground classes has an adverse effect on performance and that it can be alleviated at the batch level.

Object Detection

Imbalance Problems in Object Detection: A Review

1 code implementation31 Aug 2019 Kemal Oksuz, Baris Can Cam, Sinan Kalkan, Emre Akbas

In this paper, we present a comprehensive review of the imbalance problems in object detection.

Object Detection

MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network

5 code implementations ECCV 2018 Muhammed Kocabas, Salih Karagoz, Emre Akbas

In this paper, we present MultiPoseNet, a novel bottom-up multi-person pose estimation architecture that combines a multi-task model with a novel assignment method.

Human Detection Keypoint Detection +1

Localization Recall Precision (LRP): A New Performance Metric for Object Detection

3 code implementations ECCV 2018 Kemal Oksuz, Baris Can Cam, Emre Akbas, Sinan Kalkan

Moreover, we present LRP results of a simple online video object detector which uses a SOTA still image object detector and show that the class-specific optimized thresholds increase the accuracy against the common approach of using a general threshold for all classes.

Object Detection

Supervised Infinite Feature Selection

1 code implementation9 Apr 2017 Sadegh Eskandari, Emre Akbas

In this paper, we present a new feature selection method that is suitable for both unsupervised and supervised problems.

Feature Selection General Classification +1

Object Detection Through Exploration With A Foveated Visual Field

1 code implementation4 Aug 2014 Emre Akbas, Miguel P. Eckstein

Similar to the human visual system, the FOD has higher resolution at the fovea and lower resolution at the visual periphery.

Object Detection

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