5 papers · 1 filter
Prompt-Based Continual Compositional Zero-Shot Learning
Sauda Maryam, Sara Nadeem, Faisal Qureshi +1
We tackle continual adaptation of vision-language models to new attributes, objects, and their compositions in Compositional Zero-Shot Learning (CZSL), while preventing forgetting…
Compositional Zero-Shot Learning: A Survey
Ans Munir, Faisal Z. Qureshi, Mohsen Ali +1
Compositional Zero-Shot Learning (CZSL) is a critical task in computer vision that enables models to recognize unseen combinations of known attributes and objects during inference,…
TLAC: Two-stage LMM Augmented CLIP for Zero-Shot Classification
Ans Munir, Faisal Z. Qureshi, Muhammad Haris Khan +1
Contrastive Language-Image Pretraining (CLIP) has shown impressive zero-shot performance on image classification. However, state-of-the-art methods often rely on fine-tuning techni…
Attention Based Simple Primitives for Open World Compositional Zero-Shot Learning
Ans Munir, Faisal Z. Qureshi, Muhammad Haris Khan +1
Compositional Zero-Shot Learning (CZSL) aims to predict unknown compositions made up of attribute and object pairs. Predicting compositions unseen during training is a challenging…
Improving Single Domain-Generalized Object Detection: A Focus on Diversification and Alignment
Muhammad Sohail Danish, Muhammad Haris Khan, Muhammad Akhtar Munir +2
In this work, we tackle the problem of domain generalization for object detection, specifically focusing on the scenario where only a single source domain is available. We propose…