323 citations · 1.4k across the 44 of their papers we have counts for
5 papers · 1 filter
SID: Incremental Learning for Anchor-Free Object Detection via Selective and Inter-Related Distillation
Can Peng, Kun Zhao, Sam Maksoud +2
Incremental learning requires a model to continually learn new tasks from streaming data. However, traditional fine-tuning of a well-trained deep neural network on a new task will…
Faces à la Carte: Text-to-Face Generation via Attribute Disentanglement
Tianren Wang, Teng Zhang, Brian Lovell
Text-to-Face (TTF) synthesis is a challenging task with great potential for diverse computer vision applications. Compared to Text-to-Image (TTI) synthesis tasks, the textual descr…
SOS: Selective Objective Switch for Rapid Immunofluorescence Whole Slide Image Classification
Sam Maksoud, Kun Zhao, Peter Hobson +2
The difficulty of processing gigapixel whole slide images (WSIs) in clinical microscopy has been a long-standing barrier to implementing computer aided diagnostic systems. Since mo…
Faster ILOD: Incremental Learning for Object Detectors based on Faster RCNN
Can Peng, Kun Zhao, Brian C. Lovell
The human vision and perception system is inherently incremental where new knowledge is continually learned over time whilst existing knowledge is retained. On the other hand, deep…
Unsupervised Domain Adaptive Object Detection using Forward-Backward Cyclic Adaptation
Siqi Yang, Lin Wu, Arnold Wiliem +1
We present a novel approach to perform the unsupervised domain adaptation for object detection through forward-backward cyclic (FBC) training. Recent adversarial training based dom…