6 citations · 14 across the 9 of their papers we have counts for
14 papers · 1 filter
Segment Augmentation and Differentiable Ranking for Logo Retrieval
Feyza Yavuz, Sinan Kalkan
Logo retrieval is a challenging problem since the definition of similarity is more subjective compared to image retrieval tasks and the set of known similarities is very scarce. To…
Does depth estimation help object detection?
Bedrettin Cetinkaya, Sinan Kalkan, Emre Akbas
Ground-truth depth, when combined with color data, helps improve object detection accuracy over baseline models that only use color. However, estimated depth does not always yield…
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…
Transformer-Encoder Detector Module: Using Context to Improve Robustness to Adversarial Attacks on Object Detection
Faisal Alamri, Sinan Kalkan, Nicolas Pugeault
Deep neural network approaches have demonstrated high performance in object recognition (CNN) and detection (Faster-RCNN) tasks, but experiments have shown that such architectures…
Spatio-Temporal Analysis of Facial Actions using Lifecycle-Aware Capsule Networks
Nikhil Churamani, Sinan Kalkan, Hatice Gunes
Most state-of-the-art approaches for Facial Action Unit (AU) detection rely upon evaluating facial expressions from static frames, encoding a snapshot of heightened facial activity…