33 citations · 60 across the 24 of their papers we have counts for
7 papers · 2 filters
FA-RPN: Floating Region Proposals for Face Detection
Mahyar Najibi, Bharat Singh, Larry S. Davis
We propose a novel approach for generating region proposals for performing face-detection. Instead of classifying anchor boxes using features from a pixel in the convolutional feat…
AutoFocus: Efficient Multi-Scale Inference
Mahyar Najibi, Bharat Singh, Larry S. Davis
This paper describes AutoFocus, an efficient multi-scale inference algorithm for deep-learning based object detectors. Instead of processing an entire image pyramid, AutoFocus adop…
Universal Adversarial Training
Ali Shafahi, Mahyar Najibi, Zheng Xu +3
Standard adversarial attacks change the predicted class label of a selected image by adding specially tailored small perturbations to its pixels. In contrast, a universal perturbat…
Generate, Segment and Refine: Towards Generic Manipulation Segmentation
Peng Zhou, Bor-Chun Chen, Xintong Han +4
Detecting manipulated images has become a significant emerging challenge. The advent of image sharing platforms and the easy availability of advanced photo editing software have re…
Soft Sampling for Robust Object Detection
Zhe Wu, Navaneeth Bodla, Bharat Singh +3
We study the robustness of object detection under the presence of missing annotations. In this setting, the unlabeled object instances will be treated as background, which will gen…
SNIPER: Efficient Multi-Scale Training
Bharat Singh, Mahyar Najibi, Larry S. Davis
We present SNIPER, an algorithm for performing efficient multi-scale training in instance level visual recognition tasks. Instead of processing every pixel in an image pyramid, SNI…