collaborators

5 papers

cs.CV2025

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…

cs.CV2025

CascadedViT: Cascaded Chunk-FeedForward and Cascaded Group Attention Vision Transformer

Srivathsan Sivakumar, Faisal Z. Qureshi

Vision Transformers (ViTs) have demonstrated remarkable performance across a range of computer vision tasks; however, their high computational, memory, and energy demands hinder de…

cs.CV2025

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,…

cs.CV2025

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…

cs.CV2024

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…