140 citations · 820 across the 54 of their papers we have counts for
7 papers · 1 filter
RankGAN: A Maximum Margin Ranking GAN for Generating Faces
Rahul Dey, Felix Juefei-Xu, Vishnu Naresh Boddeti +1
We present a new stage-wise learning paradigm for training generative adversarial networks (GANs). The goal of our work is to progressively strengthen the discriminator and thus, t…
Deep Recurrent Level Set for Segmenting Brain Tumors
T. Hoang Ngan Le, Raajitha Gummadi, Marios Savvides
Variational Level Set (VLS) has been a widely used method in medical segmentation. However, segmentation accuracy in the VLS method dramatically decreases when dealing with interve…
Bounding Box Regression with Uncertainty for Accurate Object Detection
Yihui He, Chenchen Zhu, Jianren Wang +2
Large-scale object detection datasets (e.g., MS-COCO) try to define the ground truth bounding boxes as clear as possible. However, we observe that ambiguities are still introduced…
Perturbative Neural Networks
Felix Juefei-Xu, Vishnu Naresh Boddeti, Marios Savvides
Convolutional neural networks are witnessing wide adoption in computer vision systems with numerous applications across a range of visual recognition tasks. Much of this progress i…
Ring loss: Convex Feature Normalization for Face Recognition
Yutong Zheng, Dipan K. Pal, Marios Savvides
We motivate and present Ring loss, a simple and elegant feature normalization approach for deep networks designed to augment standard loss functions such as Softmax. We argue that…
Seeing Small Faces from Robust Anchor's Perspective
Chenchen Zhu, Ran Tao, Khoa Luu +1
This paper introduces a novel anchor design to support anchor-based face detection for superior scale-invariant performance, especially on tiny faces. To achieve this, we explicitl…
Non-Parametric Transformation Networks
Dipan K. Pal, Marios Savvides
ConvNets, through their architecture, only enforce invariance to translation. In this paper, we introduce a new class of deep convolutional architectures called Non-Parametric Tran…