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Found 4 papers, 1 papers with code
Few-Shot Class-Incremental Learning from an Open-Set Perspective
The continual appearance of new objects in the visual world poses considerable challenges for current deep learning methods in real-world deployments.
FaceCook: Face Generation Based on Linear Scaling Factors
With the excellent disentanglement properties of state-of-the-art generative models, image editing has been the dominant approach to control the attributes of synthesised face images.
DIODE: Dilatable Incremental Object Detection
In this paper, we aim to alleviate this performance decay on multi-step incremental detection tasks by proposing a dilatable incremental object detector (DIODE).
Faces à la Carte: Text-to-Face Generation via Attribute Disentanglement
Text-to-Face (TTF) synthesis is a challenging task with great potential for diverse computer vision applications.
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