3 citations · 4 across the 7 of their papers we have counts for
3 papers · 1 filter
Segment Anyword: Mask Prompt Inversion for Open-Set Grounded Segmentation
Zhihua Liu, Amrutha Saseendran, Lei Tong +8
Open-set image segmentation poses a significant challenge because existing methods often demand extensive training or fine-tuning and generally struggle to segment unified objects…
An Image is Worth Multiple Words: Discovering Object Level Concepts using Multi-Concept Prompt Learning
Chen Jin, Ryutaro Tanno, Amrutha Saseendran +2
Textural Inversion, a prompt learning method, learns a singular text embedding for a new "word" to represent image style and appearance, allowing it to be integrated into natural l…
Multi-Class Multi-Instance Count Conditioned Adversarial Image Generation
Amrutha Saseendran, Kathrin Skubch, Margret Keuper
Image generation has rapidly evolved in recent years. Modern architectures for adversarial training allow to generate even high resolution images with remarkable quality. At the sa…